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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d43463d9d2268247051ccea445444689d091aace | 7f2f87ede305731816bbbb76e2d7fd605e0d966f | /analise-preditiva-credit-card.r | c9ca1d7b34ade54d9b51ea4bc4becda1a8b663eb | [] | no_license | junqueira/azure-ml | ee9b0111d2dc58255afc765037786c58d9ab8e34 | ef2c2c154bcbfa7c295abc79f2b601093316735b | refs/heads/master | 2020-03-26T19:04:42.646531 | 2018-09-02T13:47:54 | 2018-09-02T13:47:54 | 145,247,678 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,994 | r | analise-preditiva-credit-card.r | library("RCurl")
library("rjson")
# Accept SSL certificates issued by public Certificate Authorities
options(RCurlOptions = list(cainfo = system.file("CurlSSL", "cacert.pem", package = "RCurl")))
h = basicTextGatherer()
hdr = basicHeaderGatherer()
req = list(
Inputs = list(
"input1... |
01c9423cfbe3b5b96ffc2af01c55eec74757137c | d7233bc626c84dee685eada4632075f9c060f4a2 | /tweet_stream.R | 62011404f33b3afba085acdef5b8ab66efded138 | [] | no_license | jasoncanney/DataAnalytics_Public | 036d37c6371896685930c5bd5581abf34374ce49 | e0bec3a597fa266ce1e6c8d474dfbea14856c5a4 | refs/heads/master | 2021-01-20T21:35:03.678295 | 2017-08-29T14:58:53 | 2017-08-29T14:58:53 | 101,771,454 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,768 | r | tweet_stream.R | # Description: This file is meant to recreate the tweetstream.py in R.
# It loads necessary packages, makes a connection to Twitter api and
# then captures tweets based on your search string
# Author: Jason Canney
# Date: 11/05/2014
# ------ Execute sections of code as instructed by highlight... |
2bba61544c68476fbfe042bedc00df43711f178c | d6ab4726dfa802b465117ac81e480b58ec54cd3e | /man/is_big_endian.Rd | 06b1b20e3fc4caf7b07100cce5fdafc2d4bbb4b5 | [] | no_license | zbarutcu/qs | 60c288f1ab9ca47bea63bf51dc258b6985cbdecd | ee080cdc8b6f1d8a94b1229e8ffb5d0f5b6fb501 | refs/heads/master | 2023-03-21T00:15:14.978802 | 2021-03-20T07:23:11 | 2021-03-20T07:23:11 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 601 | rd | is_big_endian.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/help_files.R
\name{is_big_endian}
\alias{is_big_endian}
\title{System Endianness}
\usage{
is_big_endian()
}
\value{
`TRUE` if big endian, `FALSE` if little endian.
}
\description{
Tests system endianness. Intel and AMD based systems are littl... |
6a1b2f88b9244deed71d4f1c762fc4b9348a4326 | 99b903076bd1a723c9f0bef40e76b6ba21024344 | /tests/testthat/test_proximity_matrix.R | 0a6f210c93083d6be4415c6343089163598cdc01 | [] | no_license | bbest/prioritizr | f61962f2dd32bd350b7dd3d4880ce3c3c0373fc2 | 814d0ec1cdfea6bffe0ac8208e8bf28f62475662 | refs/heads/master | 2022-06-04T19:57:43.122107 | 2022-04-25T05:16:21 | 2022-04-25T05:16:21 | 185,241,796 | 0 | 0 | null | 2019-05-06T17:28:35 | 2019-05-06T17:28:34 | null | UTF-8 | R | false | false | 7,284 | r | test_proximity_matrix.R | context("proximity matrix")
test_that("RasterLayer (adjacent non-NA pixels are proximal)", {
# data
x <- raster::raster(matrix(c(NA, 2:9), ncol = 3),
xmn = 0, ymn = 0, xmx = 3, ymx = 3)
m <- proximity_matrix(x, distance = 1)
s <- boundary_matrix(x)
s[s > 0] <- 1
Matrix::diag(s) <- 0
... |
37e5dc4c7679bffbd18a8f8196a1baba3a82a465 | b5f9a63e54964eec69cdbb5c6f18c420cbacc577 | /Scripts/BSB_MiraRiver_OverWintering_Migration_Temperature_plots.R | ae2342afdb395eb7ea84373c90c7d5873ce61396 | [] | no_license | BuhariwallaCF/Thesis-Tracking-Chapter | 2c6fed601d6dd1a91001c3a57af4ed664474efcb | 9cd1f6c4cf323582ba68710445c5515436c9467b | refs/heads/master | 2020-04-15T12:46:52.265236 | 2016-11-07T17:25:39 | 2016-11-07T17:25:39 | 62,088,810 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 6,628 | r | BSB_MiraRiver_OverWintering_Migration_Temperature_plots.R | #2016-10-19 Colin F Buhariwalla
# OVERWINTERING - plot departure/arrival times with temperature across years
# last updated:
# This script is meant to plot the overwintering departure/return events from Albert bridge into the OW area + Leaving overwintering area
# I need: 1) Temperature at BSB MR07 from Hobo Temp Log... |
d88f2a6faab02811ebf33fd251c3c6db12fdc058 | 631447642ac9cedef030c952a1cf752c3fdb0a3e | /Melanoma_Survival/server.R | a2c716dfc35cb4d7fe6c7de1c5d5f38da99c8564 | [] | no_license | droogdim83/dataProducts_Melanoma | 248a41b92f911a2356674e7882d7e7d12901942a | 448ad8265ee4122e54c21eaf6f017f2d7172d718 | refs/heads/master | 2021-01-20T07:18:56.752407 | 2017-08-27T05:05:52 | 2017-08-27T05:05:52 | 101,531,000 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,111 | r | server.R | library(shiny)
library(MASS)
library(caret)
data("Melanoma")
Melanoma$status <- as.factor(Melanoma$status)
levels(Melanoma$status) <- c("Died_Melanoma", "Alive", "Died_Other_Causes")
Melanoma$sex <- as.factor(Melanoma$sex)
levels(Melanoma$sex) <- c("Female","Male")
Melanoma$year <- as.factor(Melanoma$year)
Melanom... |
ab6e9c699b6239119896aeeba2e537289e0cbf56 | 1203cc14b7416390beb8149c3a75c28c9177a681 | /scripts/partnership_transactions.R | 9740334f99d94f0e9c4b785bf32445544576be49 | [] | no_license | AZASRS/DB_R_Testing_Environment | 7801fc9bcf078be259ed8ef80335729623bdb1dd | bf65706a2244dc67e63cd25382488d2219756b11 | refs/heads/master | 2020-03-20T06:49:08.414225 | 2018-07-27T00:31:20 | 2018-07-27T00:31:20 | 137,261,803 | 0 | 1 | null | 2018-07-16T22:23:26 | 2018-06-13T19:33:14 | R | UTF-8 | R | false | false | 2,315 | r | partnership_transactions.R | library('tidyverse')
partnership_transactions = function(){
Fund.raw = read_delim("data/201805 - Partnership_Investment_Transaction_Download.csv", delim = "|")
df_group_fees = Fund.raw %>%
transmute(`Asset Class` = `FUND_SHORT_NAME`,
`Fund Name` = `INVESTMENT_NAME`,
Date = `... |
cbeea2d69b243dd45fbd07d920d229125a4a0ccc | c42b40622b8b1a1305a0fc99ecc2c365cb994816 | /sna_script.r | b70e40b2646652872a15f01bd352ffa7210e81ff | [] | no_license | gourabchanda1990/SNA | f7af7233853c2964fbd4a5c85ebb3fbd00f96222 | c79df98adbb8dc4e96f81afd6e94b954d651479e | refs/heads/master | 2020-04-24T18:25:43.800752 | 2019-02-23T09:50:14 | 2019-02-23T09:50:14 | 172,179,281 | 1 | 0 | null | 2019-02-23T10:31:59 | 2019-02-23T06:19:29 | R | UTF-8 | R | false | false | 483 | r | sna_script.r | #load the required packages into the R Script
packages.req <- c("igraph","sna","dplyr","stringr","dplyr","ggplot2","network","reader")
packages.diff <- setdiff(packages.req,rownames(installed.packages()))
if(length(packages.diff)>0){
install.packages(packages.diff)
}
invisible(sapply(packages.req,library,character.o... |
724f2358ef0ab3b540d21af64936b9971d9a18ac | 86f7d5a0c079d7422cfad5774f3e4910b0e1a263 | /Old code/reduced.plots.R | 9c1e979189b8f177fee384da5d3a9b4dd5218182 | [] | no_license | peterbenmeyer/MeyerPlanes | 03fc66e48c44fd32a714c9cd87d7a321b610c323 | 4be7b2d6ae82c537d15b6860d16547a58aed1697 | refs/heads/master | 2020-12-24T23:28:42.428557 | 2012-11-17T00:32:23 | 2012-11-17T00:32:23 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,910 | r | reduced.plots.R | library(plyr)
library(ggplot2)
# Expects working directory set to "MeyerPlanes"
reduced.path <- file.path(getwd(), "Data", "Patents", "patents_small.csv")
reduced.df <- read.csv(file = reduced.path, as.is = TRUE, header = FALSE)
# --- define languages in order listed in file ---
langs.str <- c('Britain','Germany','Fr... |
39abbb89cc16f9a23b76d5c370ac79ea1972be95 | 4f99d63538e2ef3c97c7e72837247311e49c6019 | /script/detect-backout-commits.R | ac7d873b3fee5d97d85eceefd136acb397151928 | [] | no_license | rodrigorgs/withdrawal-firefox | 724869530079fbaf4a4673429e4b87fff1f8f8d3 | d54e0d3a9a5ca5055fc61135cc1959b5f71bf530 | refs/heads/master | 2016-09-06T18:43:34.078152 | 2014-12-01T09:38:28 | 2014-12-01T09:38:28 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,143 | r | detect-backout-commits.R | rm(list=ls())
library(dplyr)
library(stringr)
source("../lib/unlist-column.R")
commits <- readRDS("../data/firefox-commits.rds")
###
commits$bug_fixed <- str_match(commits$message, "(?i)^ *bug *([0-9]{5,6})\\b")[,2]
#' # Find the bugs backed out by each backout commit
#' First, let's threat the case where the comm... |
ae38bbccb9f84a0ee5b60e4aa940158dbf99a922 | decd805a323a5bdb863f9d5501c2963a4fb51ba0 | /MarketSimulator/R/Orders.R | 26e4e19752095c136323b9968c14474a7e9dd378 | [] | no_license | markhocky/MarketSimulator | eda0d2d11f01c480cc7a40506ae695284b77fee5 | d7000d90bc822521cc084b4c245321c565b716b5 | refs/heads/master | 2016-08-09T20:51:56.167101 | 2016-04-09T01:56:27 | 2016-04-09T01:56:27 | 55,815,590 | 0 | 3 | null | null | null | null | UTF-8 | R | false | false | 13,356 | r | Orders.R | #'
#' Parent object from which different Order types may be derived.
#'
setClass("Order",
representation(
instrument = "character",
ID = "character",
status = "OrderStatus",
quantity = "integer",
execution.price = "xts",
txn.cost.model = "function",
submission.time = "POSIXct",
... |
5d38657b0a7f28d18d956a83766c9afb0c9ada19 | 5b361b730ddba75ede1111b3da7b1c04b4df75d3 | /plot3.R | fcf369a8b532c5d0799d889af36442e21155cb09 | [] | no_license | akumar98/ExData_Plotting1 | 2c1845a67c2b730b05d69f0bea462e8efcf12183 | f0a8a4f475f531dfa40b1af9d4efb1a35fc19244 | refs/heads/master | 2020-12-28T14:51:29.946535 | 2014-12-06T05:11:45 | 2014-12-06T05:11:45 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,177 | r | plot3.R | ##Read the Txt file
powerconsumption <- read.table("./data/household_power_consumption.txt", sep=";", stringsAsFactors=FALSE, dec=".", header=TRUE)
##Create a subset with only days "1/2/2007" and "2/2/2007"
powersubset<-powerconsumption[powerconsumption$Date %in% c("1/2/2007", "2/2/2007"),]
##Create Date with Time Ob... |
d5a273dd808621800be559f07eee7cd5f11b2196 | 0266f06762c63dc2e742ae26e1a636246f999089 | /man/sim_sptree_bdp_time.Rd | e1770725b539682a50ac59c6dd3b4b27cdbab445 | [] | no_license | jjustison/rtreeducken | eedc498564140d43a6ddb39aefb76d47e13565d9 | b5a4c4092912f2db17a336ebb711c0b555126c32 | refs/heads/master | 2022-08-31T08:15:14.519329 | 2020-05-11T20:49:17 | 2020-05-11T20:49:17 | 263,359,298 | 0 | 0 | null | 2020-05-12T14:23:21 | 2020-05-12T14:23:21 | null | UTF-8 | R | false | true | 1,179 | rd | sim_sptree_bdp_time.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{sim_sptree_bdp_time}
\alias{sim_sptree_bdp_time}
\title{Simulates species tree using constant rate birth-death process to a time}
\usage{
sim_sptree_bdp_time(sbr_, sdr_, numbsim_, t_)
}
\arguments{
\item{sbr_}{species birt... |
aa3f052d13fbb088d3b073929d06ef188397e2c7 | ede41b362f24057224cbcd608695ad2ad2a0144c | /packages/oldWeather5/R/oldWeather5.R | 3f36de39430cbc551a4a818aec951ba75f277495 | [] | no_license | oldweather/oldWeather5 | 57ac0a899ea5e3ee811decd2a452aec7e59ffd50 | fc0eeda44e8bd4aae99ce545f4dec9d1bce2823e | refs/heads/master | 2020-04-06T10:03:03.464364 | 2016-11-10T17:11:16 | 2016-11-10T17:11:16 | 48,338,644 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 553 | r | oldWeather5.R | #' oldWeather5 - Process data for Panoptes oldWeather
#'
#' Reads the data files downloaded from
#' http://www.zooniverse.org/lab/1253/data-exports (project data) &
#' http://www.zooniverse.org/lab/28/data-exports (Talk data).
#'
#' @section functions:
#' \itemize{
#' \item \code{\link{ReadClassifications}} - Get ... |
3f797ea721d6e8e39ce0d3f002ebab556dca7214 | 163d25753fbb4d5042f744f9379e7df7c004988b | /R/ggtaugplot.R | e1deb49445f2ece837d17558a99b59768639c832 | [] | no_license | cran/tensorBSS | bafb41acdad89b11c2f33f4c307f64991bc39e9c | 14be1b8df1f3d6a4bcfe4dac13f048198e927cac | refs/heads/master | 2021-06-20T06:19:24.496911 | 2021-06-02T05:20:02 | 2021-06-02T05:20:02 | 66,539,007 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,561 | r | ggtaugplot.R | ggtaugplot <- function (x, crit = "gn", type = "l", scales = "free", position = "horizontal",
ylab = crit, xlab = "component", main = deparse(substitute(x)),
...)
{
crit <- match.arg(crit, c("gn", "fn", "phin",
"lambda"))
position ... |
6c6e8aca170e2932b180eacc7e38c6182655f2b5 | acfc4a18c41c8bcd76ff898ec3899b9e59737474 | /R/Prices.MB.R | f80a036eebcd00e10fb063e46a5c1b0fa937c38c | [] | no_license | tomvar/bundling | 8a2d135b69973df75320d2a78ba2a7457147af71 | e8fc6e6a1f7b006a3d9ff59a33bb795bbf677a15 | refs/heads/master | 2021-01-10T21:54:43.301831 | 2018-03-14T16:22:51 | 2018-03-14T16:22:51 | 39,305,990 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,486 | r | Prices.MB.R | #' This function creates a vector of combination from sequences of prices p.1, p.2 and pb
#' It will be searched to find prices that maximize profits in MB strategy
#'
#' @param p.1.min.max Minimum and maximum value of price p1 [p.1.min.max <- c(p.1.min, p.1.max)]
#' @param p.2.min.max Minimum and maximum value of pric... |
ae6c18aea41601c342df9ed8e8c5df6db02ecc6d | c31ccca5b190016df5d85ad36d5dcfeb2c1dadde | /man/cell_extract_spatial.Rd | 9a1f28129a28770a3e9039b16465add6559bf2fa | [] | no_license | tremenyi/AgroClimGrapeIndices | 837116651acac560c81bc8ae406eb529fb89ce09 | e4e702b1a6eabb14e048e1fbd7f3616595f66638 | refs/heads/master | 2020-03-11T01:20:50.340888 | 2018-04-16T06:06:42 | 2018-04-16T06:06:42 | 129,689,224 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 827 | rd | cell_extract_spatial.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ACGI_functions.R
\name{cell_extract_spatial}
\alias{cell_extract_spatial}
\title{Spatial cell extract}
\usage{
cell_extract_spatial(raster_filename, spatial_layer, subset_layer = NULL,
fun_list = list(mean = mean, var = var, n = length))
}
... |
9320fcafd7c988cb1222d1727364ef9eeaacaff4 | c9777199c78b32abc5230b74430312a6fe044bd8 | /man/tabSERE.Rd | 97323ca6c20d19a8c3a51d50cebc20b7fe052640 | [] | no_license | PF2-pasteur-fr/SARTools | 114b64482549b6f91512ee7e63402be6e0717c74 | 3e504afd40caaa62bd6b75b7f0cfca34f6daa65e | refs/heads/master | 2023-06-22T23:28:32.002032 | 2022-03-23T09:21:09 | 2022-03-23T09:21:09 | 27,759,216 | 112 | 70 | null | 2022-03-23T09:21:10 | 2014-12-09T09:31:15 | R | UTF-8 | R | false | true | 403 | rd | tabSERE.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tabSERE.R
\name{tabSERE}
\alias{tabSERE}
\title{SERE statistics for several samples}
\usage{
tabSERE(counts)
}
\arguments{
\item{counts}{\code{matrix} of raw counts}
}
\value{
The \code{matrix} of SERE values
}
\description{
Compute the SERE ... |
9962097160544f589d227347c3d03e94e462ac2b | abf39cb642af0fdaf237a37ea84e5875a8ce0d29 | /plot3.R | 1e3878e1ed84dd1fe2f6531a1b4d979bad28d91b | [] | no_license | xuxiao0330/ExData_Plotting1 | 3e0239ed9a586e77c72aa1be1deeca7356b77180 | 9d7b5b56177cf623dc149db4f7fd5cfdede2588c | refs/heads/master | 2020-12-25T17:05:37.625844 | 2016-01-11T15:20:36 | 2016-01-11T15:20:36 | 42,379,508 | 0 | 0 | null | 2015-09-13T01:31:52 | 2015-09-13T01:31:52 | null | UTF-8 | R | false | false | 949 | r | plot3.R | <<<<<<< HEAD
#reading table
dt <- read.table("household_power_consumption.txt",sep=";",header = TRUE,stringsAsFactors=FALSE)
#making date format
dt$Date <- as.Date(dt$Date,format="%d/%m/%Y")
#subsetting 2007-02-01 ~ 2007-02-02
dt1 <- subset(dt,dt$Date == "2007-02-01"|dt$Date =="2007-02-02")
#Setting time in dt1
dt1$Tim... |
8e669e38db11e989f60f13646ac0acb8f1f799b1 | e33b78e73c726c361d4e7c66f01df56f63f7a76c | /TIDYR.R | 33980c8423cbf3da0d068bbaa5270d47bb9d6b9c | [] | no_license | Shalini-cmd/hello-world | cf4fc16e037ecb732d55232ebf6e9f6e127864a4 | 075ce2f7912f20f38da4c55b71b7593b2260fd63 | refs/heads/master | 2021-03-10T13:04:58.081805 | 2020-05-20T05:13:27 | 2020-05-20T05:13:27 | 246,455,821 | 0 | 0 | null | 2020-03-11T02:41:27 | 2020-03-11T02:27:38 | null | UTF-8 | R | false | false | 3,580 | r | TIDYR.R | #three rules for tidy dataset
#1. Each variable should have a column
#2. Each pbservation must have its own row
#3. Each value must have its own cell
table1%>%
group_by(year,country)%>%
summarize(n_cases=sum(cases))
table1%>%
group_by(country)%>%
mutate(per_cases=sum(cases)*10000/sum(population))
#Spr... |
29e37f932c8f857c70f97b710a133f82d039335e | 1aa413301db92dd918278f7d309260b0130f8cd8 | /R/plot_rendite_comp.R | 87183291d2878c3eed62f4d22e70e6c9c3d73dd5 | [] | no_license | philgee1981/btcecho | 19467886cb335ddd3a6f28e67ac3edf883d979ab | 37b01871ecb72da58e11643394c89428b9c8adf9 | refs/heads/master | 2022-01-10T01:23:24.811566 | 2019-05-27T15:50:27 | 2019-05-27T15:50:27 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,095 | r | plot_rendite_comp.R | #' Plot Returns of different portfolios
#'
#' Plot one portfolio-development in comparison to two other ones
#'
#' @param returns_safe A xts with several columns consisting of data
#' @param portf_safe A vector defining the portfolio weights
#' @param returns_medium A xts with several columns consisting of data
#' @par... |
aeaa0c318c79871dd7daf976b27e3f2721c86605 | 9afab26de81a32255d270beb335543d73759e4f0 | /Practica2/Ejercicio3/Ejercicio3.R | 597eafcfec1d02f37ad3486f0580587567c34ee0 | [] | no_license | Llampi/Probabilidad-y-estadistca | aa6a8f1506d4aae24f42991388f99a319cfde43b | f89fee10e3b94bf0baf09732e50a1059acce28d8 | refs/heads/master | 2020-03-09T21:03:08.615779 | 2018-06-01T13:17:46 | 2018-06-01T13:17:46 | 128,999,776 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,273 | r | Ejercicio3.R | ###PREG3
#Preg3.a
vec1 <- c(2,1,1,3,2,1,0)
vec2 <- c(3,8,2,2,0,0,0)
#Aqui vec1[1]=2, vec2[2]=8, entonces el la condicion vec1[1]+vec2[2]=10 es verdadera, por lo que se imprimira el mensaje
if((vec1[1]+vec2[2])==10){ cat("Imprime el resultado!") }
#vec1[1]=2,vec2[1]=3, como ambos enunciados son verdaderos, el mensaje ... |
97a9d292fb7faef359ef87b2c0f8598297f22b91 | 2e5bcb3c8028ea4bd4735c4856fef7d6e46b5a89 | /man/getXAM.ChipEffectFile.Rd | 4c9082764e6c7fc97d2ac264d8f54f30092e9d47 | [] | no_license | HenrikBengtsson/aroma.affymetrix | a185d1ef3fb2d9ee233845c0ae04736542bb277d | b6bf76f3bb49474428d0bf5b627f5a17101fd2ed | refs/heads/master | 2023-04-09T13:18:19.693935 | 2022-07-18T10:52:06 | 2022-07-18T10:52:06 | 20,847,056 | 9 | 4 | null | 2018-04-06T22:26:33 | 2014-06-15T03:10:59 | R | UTF-8 | R | false | false | 1,663 | rd | getXAM.ChipEffectFile.Rd | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Do not modify this file since it was automatically generated from:
%
% ChipEffectFile.xam.R
%
% by the Rdoc compiler part of the R.oo package.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\name{getXAM.ChipEffe... |
2e28959006ababb0cc63fb3f98aa9fb6df0b78b2 | d5fd9fcb1f81093a5d16184b889cf74edd985b2e | /haskell/statisticsScripts/rq4_tests.R | 0787366b8c35bff0a2d9e16117376af8cad3a450 | [] | no_license | doyougnu/VSat | 90e4f55a67f420e87e833bc94fd65d4b3263af29 | 4c9acbd1280792c0e9665da737131ebf2d9ea0aa | refs/heads/master | 2021-10-11T06:10:34.149842 | 2021-10-01T13:35:43 | 2021-10-01T13:35:43 | 105,307,042 | 4 | 1 | null | 2018-07-12T17:02:33 | 2017-09-29T18:56:43 | Haskell | UTF-8 | R | false | false | 5,629 | r | rq4_tests.R | library(ggplot2)
library(dplyr)
library(tidyr)
library(broom)
library(scales)
finRawFile <- "../munged_data/financial_raw_singletons.csv"
autoRawFile <- "../munged_data/auto_raw_singletons.csv"
finRawDF <- read.csv(file=finRawFile) %>%
mutate(Algorithm = as.factor(Algorithm), Config = as.factor(Config)) %>%
muta... |
44a43d3fb75fb4d471b2be6e7045eeb1c09b52c4 | d431a10beb2e7f84ca6765c3d91bf5057196afb2 | /Ecological Modelling/MatrixModel/LeslieMatrix.R | d2f48b5f6e61554288177b42be640a01b989de52 | [] | no_license | yaghan/bio7_examples | 89d0de241e6e58dc9f37cee5b777f6dd63d96281 | 3815086a3500cdf1026c2652ed726e5575a14d15 | refs/heads/master | 2021-01-16T22:07:32.996426 | 2015-05-21T15:20:43 | 2015-05-21T15:20:43 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 377 | r | LeslieMatrix.R | # Start the RServer and then interpret the source!
# Open the Expression dialog and then enter
# n1 to see the results in the console !
L<-matrix(0,nrow=4,ncol=4)
#Birth-rates
L[1,]<-c(0,4,3,1)
#Probability of survival
L[2,1]<-0.7
L[3,2]<-0.9
L[4,3]<-0.5
#Abundance
n0<-c(9,5,4,2)
#Abundance after one ... |
b93c7b989c56e5bc9ce4ccf7583387c52b8411e8 | 8cd239031820b73aa8b6a7400c9651d8a80ba043 | /plot4.R | 07486f44303e140c4af9fae744dbe1c50af83a8c | [] | no_license | radh07/ExData_Plotting1 | 84fc80437648fc6d5f6144926fe8e7ccf79882f9 | 25504a1c678f8dcdb5bd0c952a20c604fda578b4 | refs/heads/master | 2021-01-18T08:49:36.675456 | 2015-03-04T18:45:21 | 2015-03-04T18:45:21 | 31,574,854 | 0 | 0 | null | 2015-03-03T02:19:16 | 2015-03-03T02:19:16 | null | UTF-8 | R | false | false | 1,832 | r | plot4.R | # Read the data into R
data<-read.csv(file="household_power_consumption.txt", header=TRUE,sep=";",colClasses="character")
# Grab the data for the two dates of interest
relData<-subset(data, Date == "1/2/2007" | Date == "2/2/2007")
# Combine the Date and Time columns into a single time object using as.POSIXct
timeobj ... |
4cb0b7512b70cf5876691a4754fddb55236d32ac | fed93c5054545d927f3695b51f3a8c9dafb90086 | /R/tagtools/R/hilbert_env.R | 5be8984de3cb139298c90ccc734e6e8f206df220 | [] | no_license | spluque/TagTools | 34629e360afd3170aa167437cccfd72001b2c69c | 5f150109114cbbdf551cbf8a02e335006613d332 | refs/heads/master | 2021-12-07T10:54:11.656760 | 2021-10-14T20:36:29 | 2021-10-14T20:36:29 | 233,162,704 | 0 | 0 | null | 2020-01-11T02:11:30 | 2020-01-11T02:11:29 | null | UTF-8 | R | false | false | 2,224 | r | hilbert_env.R | #' Compute the envelope of X using Hilbert transform.
#'
#' Compute the envelope of the signal matrix X using the Hilbert transform.
#' To avoid long transforms, this function uses the overlap and add method.
#'
#' @param X a vector or matrix of signals. If X is a matrix, each column is treated as a separate sign... |
2380239725d28a83f05776f86e3f9ea98c016705 | f1b04a74ebfe7b0023d3d3c9af14791a4c2eef22 | /R/call_coaccessible.R | b0bbe5d49070324fd82c8af8b9f58a088d175824 | [
"MIT"
] | permissive | Zeyu618/maize_single_cell_cis_regulatory_atlas | 2a98385f0ddde5e534a4c01f0ce4e1798aec1cdd | 3178a0c2458d9fe229635b1bd94902f579518c12 | refs/heads/master | 2023-05-02T07:12:54.782679 | 2020-10-08T12:32:25 | 2020-10-08T12:32:25 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,884 | r | call_coaccessible.R | ###############################################################################
## Cicero trajectories
###############################################################################
# default variables
threads <- 1
dims <- 50
# commandline arguments
args = commandArgs(TRUE)
if(length(args)==4){
# read in co... |
4968e3dc292b829f834c3d15d04637b24525b8e8 | 324f2e9fab245df3190adacd93de54eb313c23cf | /ui.R | f0cc003205cc58c068b57e609ed850a8bc2f347c | [] | no_license | Yambcn/Shiny-Application | c46c3a36d3c81c7ae6613b7697af09d8b46557a7 | 5696282e3929f670f01c5941a40b6b0380550c70 | refs/heads/master | 2020-05-31T03:50:09.858800 | 2014-08-24T10:03:17 | 2014-08-24T10:03:17 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,624 | r | ui.R | library(shiny)
shinyUI(pageWithSidebar(
headerPanel("Calculation of the total cost of a Loan"),
sidebarPanel(
h4('Introduction / Documentation'),
h5('The goal of this application is to calculate to cost of amortization of a
loan. In this application just amortization for fixed loans could be
... |
46756b42cc262c7a98c4fea524dcbc3d2c22ad83 | e596c317d5f14ec9675b4b245d08a5e13a550f8b | /sipp.R | eed035413247fc8d9609262c1100223e59c248e9 | [
"MIT"
] | permissive | jw3315/CensusSIPP | 03c47770afdfb57e47597ee3b328ea5ca4714246 | a242b711613b814264eadc0fa4bb746a6e872b0f | refs/heads/master | 2020-03-28T02:32:29.966026 | 2018-09-06T20:37:04 | 2018-09-06T20:37:04 | 147,578,171 | 5 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,321 | r | sipp.R | ## This is an example of pulling SIPP Panel 2008's 16 waves data. Unzip and manipulate it in R.
library(readr)
library(SAScii)
library(data.table)
# library(rstudioapi) # load it
# current_path <- getActiveDocumentContext()$path
# setwd(dirname(current_path ))
## pull, unzip and save the core files
save<-function(i... |
ee747f473786b23209a63d492a454cd5573ce74c | 1c814d6da3c3c612e8cafc5c337f9636eb415440 | /tests/testthat/test-save_ts.R | 0eb09020d4fc28919984668d9070a909ffe41732 | [
"MIT"
] | permissive | difiore/mapmate | 28fdcf92bf67ccc50c3c3bb63c7b337f611fa0fa | 7c36274078c4b6ffbd9dcc278f3176b7535ba86f | refs/heads/master | 2022-01-09T03:26:22.252531 | 2018-05-05T23:37:50 | 2018-05-05T23:37:50 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,129 | r | test-save_ts.R | library(mapmate)
suppressMessages(library(dplyr))
context("save_ts [functions.R]")
data(annualtemps)
temps <- mutate(annualtemps, frameID = Year - min(Year) + 1) %>%
group_by(Year, frameID) %>% summarise(z=mean(z))
xlm <- range(temps$Year)
ylm <- range(temps$z)
g1a <- save_ts(temps, "Year", "z", id="frameID", cap=r... |
bf754289a4e749daa13ea1a3a89d4fdce23c54d2 | 829e9ea609fff4c100edc4140c3aa528edc58973 | /heterogeneity/SNonparaAnalysis.R | 8dbbd0d22e484f834d1ce2589126d6c31d8a5fda | [] | no_license | applXcation/udacity | c4794f846812a29de0f15f68e8e43b0a165a2bfd | de522d0c31dd01e2a50837d5b9d1b7ba1f678dbe | refs/heads/master | 2021-01-11T22:12:21.788806 | 2017-01-14T13:59:54 | 2017-01-14T13:59:54 | 78,938,155 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,734 | r | SNonparaAnalysis.R | SNonparaAnalysis <- function(self.eval, v1, ..., grouping.var, moment, jointly = FALSE) {
# Simplified Non-Parametric Analysis. Takes, as an argument, the self-assessment and vignette variables, together with the grouping
# variables as a dataframe. Calculates by itself the "c" variable through NonparaComparable()... |
95058a6c7a6f6ebbf2fe6418909f21aed54b4688 | fdc4be9a687bbb9c66343cdfd72c22afd8221723 | /cachematrix.R | 581c41bcd09464156d356396cf71d9cb7c0aa9a5 | [] | no_license | ebecker54/ProgrammingAssignment2 | af5e8187472e9a20fd3d33a2a8780dce216fa81f | ca81ced008ee23f201deedf35beba2d18b39e8bb | refs/heads/master | 2020-02-26T15:26:50.956478 | 2015-10-25T16:19:07 | 2015-10-25T16:19:07 | 44,875,868 | 0 | 0 | null | 2015-10-25T16:19:08 | 2015-10-24T17:04:17 | R | UTF-8 | R | false | false | 1,070 | r | cachematrix.R | ## makeCacheMatrix and cacheSolve work by creating
## a vector of functions that create and stores
## the value of a matrix inverse, then caches its inverse
## then recalls that value from the cache or computes it
## and stores the calculation in the cache
## makeCacheMatrix function creates a list object
## with func... |
146aebe967bac488a5c1145543b99c7d2bfd0cb4 | 509919d0d70bab8a9c4e8618b7e99656948d3e6b | /lmer_vs_anova/lmer_tab.R | 79baa8aa1f5d53c047b5c43824848318384fb861 | [
"MIT"
] | permissive | debruine/proveit | 50981bd0ae9a06bcf2f1c2a9b148c5e828ff589a | 95d4842b204164308eea668a5da759d38e9dcfda | refs/heads/master | 2021-07-23T09:22:14.499489 | 2019-01-15T15:51:29 | 2019-01-15T15:51:29 | 142,279,290 | 0 | 0 | MIT | 2018-09-20T10:40:14 | 2018-07-25T09:37:38 | R | UTF-8 | R | false | false | 422 | r | lmer_tab.R | ### lmer_tab ----
lmer_tab <- tabItem(
tabName = "lmer_tab",
fluidRow(
column(
width = 4,
plotOutput(outputId = "ranef_sub_plot", height = "auto")
),
column(
width = 8,
plotOutput(outputId = "ranef_stim_plot", height = "auto")
)
),
box(
title = "VarCor",
solidHead... |
1816c6eea22a7e7e1e478916d657ea8aec7a9294 | 2553cdad83162e35aefef486816184d520302665 | /R/taxa.meansdn.R | 7368a6b65ac0aa6de42900b4564ac27341d5fa6e | [] | no_license | cran/metamicrobiomeR | b9cf404e83f0e8ae4cc024289ccca8dc1e590b56 | a55866e6cdda36d6d59a59cbd5f20baccb8bd970 | refs/heads/master | 2021-07-08T18:42:53.689765 | 2020-11-09T10:20:05 | 2020-11-09T10:20:05 | 206,034,869 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,774 | r | taxa.meansdn.R | #' Summarize abundance by group
#'
#' This function summarizes taxa/pathway abundance tables to provide mean, sd, count by groups.
#' @param taxtab taxa/pathway abundance table from phylum to species or any preferred highest taxa level.
#' @param sumvar main variable for summary
#' @param groupvar variable to be ... |
740abe8ab04af416d865f8f99982072ddedf5f32 | 0d6c580a2fd19cd76b2f94e7800278ebfffa82c9 | /src/fare_count/Plot_Perform.R | 9a6d98756edb5b6ac5f9dfaad19af585ee678eb0 | [] | no_license | haoyu987/bigdata2016taxi_weather | 38021f5e0c92b9aecff73b751200ebd12373074c | 410a9d212fd6be2baf58142737e4138701c529ff | refs/heads/master | 2020-06-15T09:41:44.148389 | 2016-05-16T21:47:30 | 2016-05-16T21:47:30 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 923 | r | Plot_Perform.R | #
# See the performance of In-Mapper Combiner v.s. Classic
#
library(ggplot2)
theme_set(theme_bw(base_size = 22))
myGthm <- theme(text = element_text(size = 25))
perf <- read.delim("src/fare_count/perform_benchmark.tab")
perf$SizeLevel <- factor(perf$Size, sort(unique(perf$Size)),
format(sort(... |
02253e98b02d3b76b47e875c3609823dc49a6f66 | f131a2e7dd6a0eee65e0fc6dc8325c95c3b19623 | /Homework/Day_2_R.R | 0fbd92cca6d081220aaa465c0ee2a452fb7453c9 | [] | no_license | EthanUWC/Intro_R_UWC | 30636212b8a86651f72a46974463e9a1d0448d0f | 90779359951fd5959bececfacf70d8c8d8252278 | refs/heads/master | 2020-04-19T09:20:06.281981 | 2019-05-14T20:11:34 | 2019-05-14T20:11:34 | 168,107,216 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,106 | r | Day_2_R.R | #plotting in R using ggplot2
# day2
#Ethan
#30/01/2019
#load libraries
library(tidyverse)
lam <- read_csv("~/R/R/data/laminaria.csv")
chicks <- datasets::ChickWeight
??ChickWeight # the "??" tells R to refer you to the help tab
ggplot(data = chicks, aes(x = Time, y = weight)) + # ggplot is a function that allows a ... |
995538bcd6a65963ea27c8ed1d8fc2f17c03b0fb | ee50ce44675c7181d1ea5bf6b9a7539f4b42cc42 | /plots.r | 5443f8aff2fc81038ab1711e6979ac221c76cb3e | [
"MIT"
] | permissive | mdthorn/nyc_restaurant_grades | 16bd3bbc93e01b25430f2b88674ac18ea447d846 | abd228588babf5fd99528d6eb8d7fa1718e6fa92 | refs/heads/master | 2020-08-01T10:56:49.453299 | 2016-11-12T20:35:01 | 2016-11-12T20:35:01 | 73,576,770 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 635 | r | plots.r | library(ggplot2)
library(reshape)
library(scales)
library(choroplethr)
ggplot(grades_by_month, aes(x=month, y=value, group=variable, color=variable)) + geom_line() +
geom_hline(aes(yintercept=avg), linetype="dashed", color="gray57") + xlab("") +
ylab("% of Restaurants with 'A' Grade") + scale_y_continuous(labels=... |
47a775fd1896914a3f0ae9a45741573701794599 | 4ed740aeec1366c7647bd599406f65ef78f7786b | /man/replace_number.Rd | f37c36abc60dc6fc5030cd424f864313e8c2f313 | [] | no_license | trinker/qdap2 | 00f97557a43eeee487c6a11074f940f0204d042c | b9244fe90c5f5cec9cd891b1ba1f55b157467e5f | refs/heads/master | 2021-01-01T17:21:41.171478 | 2013-01-29T03:55:12 | 2013-01-29T03:55:12 | 7,884,841 | 3 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,191 | rd | replace_number.Rd | \name{replace_number}
\alias{replace_number}
\title{Replace Numbers With Text Representation}
\usage{
replace_number(text.var, num.paste = "separate")
}
\arguments{
\item{text.var}{The text variable.}
\item{num.paste}{A character vector of either
\code{"separate"} or \code{"combine"}. Of
\code{"separate"} i... |
74f70999be81c2a4b4bf2997bd83a6529cd104cd | da317c3ad3a26dd1fbde456c191f41dbc438a4ef | /shiny/server.R | dd96735c4b0c1d601263c3db43556899f3feb05e | [
"MIT"
] | permissive | maxfilip98/APPR-2017-18 | e17cf82207865cf7a68cff2833ea3a26601e1dda | f9fd04f90ca6f8b711d443ea1f52b03d97ea9890 | refs/heads/master | 2021-09-06T20:00:48.464904 | 2018-02-10T18:23:54 | 2018-02-10T18:23:54 | 110,083,843 | 0 | 0 | null | 2017-11-09T07:47:04 | 2017-11-09T07:47:03 | null | UTF-8 | R | false | false | 1,597 | r | server.R | library(shiny)
function(input, output) {
output$grafi1 <- renderPlot({
tabela1 <- BDP %>% filter(drzava == input$drzava1, sestava ==input$sestava)
print(ggplot(tabela1, aes(x = leta, y = vrednost/1000)) + geom_line() +
xlab("leta")+ ylab("vrednost") +
ggtitle("Vrednost BDP-ja v ... |
ca178c4053c2afd2bc044efebfb243e1a446e5b6 | a4b8d053e3936d63c09c29a7338509c7bf49e738 | /man/add_kml.Rd | 8c43a83bc210e837ec921dcc7b6d8af628cf2cb4 | [] | no_license | ManuelDeFrancisco/googleway | 1d7b35d368579f4123b86a44c40b33a5d2b90d8b | cfc53dcf019de587f30b2f3c04648c626bc6459c | refs/heads/master | 2020-05-20T23:42:34.050917 | 2017-03-10T10:24:46 | 2017-03-10T10:24:46 | 84,547,853 | 0 | 0 | null | 2017-03-10T10:21:28 | 2017-03-10T10:21:27 | null | UTF-8 | R | false | true | 423 | rd | add_kml.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/google_map_layers.R
\name{add_kml}
\alias{add_kml}
\title{Add KML}
\usage{
add_kml(map, kml_data, layer_id = NULL)
}
\arguments{
\item{map}{a googleway map object created from \code{google_map()}}
\item{kml_data}{kml data layer}
\item{layer... |
7075cb8afa82b74e8a836ae645d54f4ed0f79b22 | a189b6b9003ae77bc2d774ea5845f4842f06f5ba | /man/summary.bootAverageDominanceAnalysis.Rd | 912089539bfb68a6798ca4b56cbd242e40b38fcb | [] | no_license | clbustos/dominanceAnalysis | 28a95b324aa65167f4556a59f4f6cfeb9ad55962 | 94846f37de1617f40d9381bd42e49c14e6717761 | refs/heads/master | 2023-05-25T13:27:37.933994 | 2023-05-12T21:13:32 | 2023-05-12T21:13:32 | 13,853,056 | 22 | 12 | null | 2020-06-20T13:18:39 | 2013-10-25T06:20:48 | R | UTF-8 | R | false | true | 630 | rd | summary.bootAverageDominanceAnalysis.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/summary.bootAverageDominanceAnalysis.r
\name{summary.bootAverageDominanceAnalysis}
\alias{summary.bootAverageDominanceAnalysis}
\title{Summary for bootAverageDominanceAnalysis.}
\usage{
\method{summary}{bootAverageDominanceAnalysis}(object, f... |
617fe8f0322ebc58dfddedab2644596e1438125b | 57854e2a3731cb1216b2df25a0804a91f68cacf3 | /tests/testthat/test-variable-type.R | 03c24b48a05ae6ffd48d0f561badb5078af17bca | [] | no_license | persephonet/rcrunch | 9f826d6217de343ba47cdfcfecbd76ee4b1ad696 | 1de10f8161767da1cf510eb8c866c2006fe36339 | refs/heads/master | 2020-04-05T08:17:00.968846 | 2017-03-21T23:25:06 | 2017-03-21T23:25:06 | 50,125,918 | 1 | 0 | null | 2017-02-10T23:23:34 | 2016-01-21T17:56:57 | R | UTF-8 | R | false | false | 1,775 | r | test-variable-type.R | context("Variable types")
with_mock_HTTP({
ds <- loadDataset("test ds")
test_that("Variable type method", {
expect_identical(type(ds[["birthyr"]]), "numeric")
expect_identical(type(ds$gender), "categorical")
})
test_that("Changing numeric type by <- makes requests", {
expect_P... |
cfed98e63adff8d2fc77fee4d169513114213bf5 | c4abf97a3641c2a3adf1ab7adab87b47a036fb86 | /TP2/plot-eje.r | 77951ba1713f58bd6b3ef94efec7d012ac780379 | [] | no_license | elopez/IAA | b35ad98cdabbcb92f8e1aa37358222acde42425d | 865838ec5e36771d2dbb849970c39133b4471786 | refs/heads/master | 2021-01-21T04:40:50.635383 | 2016-06-12T20:22:33 | 2016-06-12T20:22:33 | 54,748,275 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,206 | r | plot-eje.r | library("ggplot2")
x = read.csv("out-ej7/plot-error-after-prune.csv", header=F)
a = aggregate(x[x[,1]=='a',3:4], list(x[x[,1]=='a',2]), mean)
b = aggregate(x[x[,1]=='b',3:4], list(x[x[,1]=='b',2]), mean)
w = read.csv("out-ej7/discrete-error.csv", header=F)
ann = aggregate(w[w[,1]=='a',3], list(w[w[,1]=='a',2]), median)... |
fb6ee1a99db3b4fa7c77d0451925e22b828b469b | 5710b0ca77732f863616e6de4b8b68977bcce7a3 | /Downstream_Analysis_WGS/Allele_freq_plots.R | d6283c7b9cee47dfe47c053887610e9d118b556a | [] | no_license | mcadamme/FieldHz_Pop_Genomics | f96f566dc71c88bd3540b644adb3cbc3df23486a | bc52a6e0fe325c526ed1629508d6ddec6b0473cf | refs/heads/master | 2021-11-05T20:45:34.482927 | 2021-10-05T18:04:21 | 2021-10-05T18:04:21 | 154,679,948 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,922 | r | Allele_freq_plots.R | #This is the script I used to plot allele frequency change at Cry1 and Cry2 associated loci over time
#04122021 MF
library(tidyr); library(ggplot2)
setwd("~/Desktop/Hz_fieldColl_pop_gen/Reanalysis_PNAS")
#loading resistance-associated loci with signatures of temporal change in the field
Cry1 <- read.table("./hiCry1F... |
caceec1aa6cc0eaebf9b1d124aaf396507ac06d7 | eff0ebd361b8bb944c37771b7418e9087ad3307e | /man/with_check_disabled.Rd | da2e57cdccc4d0459bfb6e833e3f9ab423ca5824 | [
"MIT"
] | permissive | hongyuanjia/eplusbuildr | 715d0a0be7fd51ca1a68c1db5cfd1ae85a3d6b89 | f7683130fde1b128e36bd814f5f06a392189d3c0 | refs/heads/master | 2020-09-08T03:23:11.218913 | 2020-01-10T15:59:46 | 2020-01-10T15:59:46 | 221,000,646 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 530 | rd | with_check_disabled.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/with.R
\name{with_check_disabled}
\alias{with_check_disabled}
\title{Evaluate an expression with eplusr checking components disabled}
\usage{
with_check_disabled(disable, expr)
}
\arguments{
\item{disable}{Names of checking components to disa... |
72edc3675118405ef4ee3e2d6a7fdd4574b404bb | e914260953075b7b6233a936251e37d329643a38 | /cachematrix.R | 76cec6a9a0851d33b1557982da18759ebb8b6f80 | [] | no_license | mustehsanikram/ProgrammingAssignment2 | bf3788d845f836d2a5bc1c172a0da7e1f8f408b1 | 127ca37b69745ba22be1ed0de1057f65022b11a3 | refs/heads/master | 2021-01-14T09:49:47.362793 | 2019-08-06T05:18:09 | 2019-08-06T05:18:09 | 35,603,148 | 0 | 0 | null | 2015-05-14T09:35:13 | 2015-05-14T09:35:13 | null | UTF-8 | R | false | false | 1,246 | r | cachematrix.R | ## Save actual matrix and return inverse of matrix from cache,
## (if calculation is already done) or first calculate inverse,cache it and then
## return
## This function caches the actual and inverse of matrix
makeCacheMatrix <- function(x = matrix()) {
invs <- NULL
set <- function(y) {
... |
e44782cfdce1ad9302bf511b56b32de41c36657c | b86924757435aed14d06e65fed2190c71f49617d | /beiliao/server.R | dca357ae89ed3322cc7aad34ddc23fb8bea5c8b3 | [] | no_license | yichunsung/Nanhua | 06f00f3e16a33e154cec17788074c6719dfa340e | 3c25da4b481d594b435e1e823b26112dfaa97cbb | refs/heads/master | 2021-01-18T07:55:49.637059 | 2017-03-09T09:27:02 | 2017-03-09T09:27:02 | 84,296,213 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,551 | r | server.R | library(magrittr)
library(httr)
library(rvest)
library(stringr)
library(reshape2)
library(knitr)
library(ggplot2)
library(plotly)
Sys.setlocale(category = "LC_ALL", locale = "")
getDataformCWB <- function(iterm){
fromdate <- Sys.Date()-4 # "2017-01-06"
todate <- Sys.Date()-1 # "2017-01-06"
date <- seq.Date(f... |
f8d0c57d17d018298624d0c87a456e83759a3b94 | d3c1254c2aefd9978c3ef22b094c498ed738bff6 | /master.R | c25b18af019b87416eaef6e49f464d100f5ee496 | [] | no_license | joebrew/maltem_cost_effectiveness | 543d0f6ca658debee010d9c7714c9d6f60ed5048 | 8aed2fba47fae30edda30051864b20fbcfabdf4e | refs/heads/master | 2021-08-08T11:53:40.833966 | 2021-01-23T09:22:40 | 2021-01-23T09:22:40 | 79,894,422 | 3 | 1 | null | null | null | null | UTF-8 | R | false | false | 7,124 | r | master.R | # Libraries
library(tidyverse)
# BES data
source('get_bes_data.R', encoding = "UTF-8")
# Weather data
source('get_weather_data.R')
# # Lagged weather data
# source('get_wide_weather.R')
# IRS data
source('get_irs_data.R')
# ITN data
source('get_itn_data.R')
# Get population into itn
itn <-
left_join(x = itn,
... |
66352c0f3d8151dddef6d3076aa41bd9f8da4125 | 9a581658d45500655d37957dd05dd6488524ff47 | /development/R-main/unliked-markers-main-dev.R | f0814f1046d7427ad0baf9c05505c54714ee34f3 | [] | no_license | eriqande/CKMRsim | 04def67a7f82539afb918f97e81b1361c100261d | 652193e2e9e6dcac268b9816665cc2cf16f1d7ed | refs/heads/master | 2022-10-31T01:40:18.174183 | 2022-10-26T16:25:22 | 2022-10-26T16:25:22 | 55,812,404 | 11 | 6 | null | 2021-04-30T13:43:51 | 2016-04-08T22:03:36 | R | UTF-8 | R | false | false | 798 | r | unliked-markers-main-dev.R | library(dplyr)
library(CKMRsim)
library(ggplot2)
# read in the "linked mhaps" but treat them as unlinked
mhlist <- long_markers_to_X_l_list(D = linked_mhaps,
kappa_matrix = kappas[c("MZ", "PO", "FS", "HS", "U"), ])
# add the matrices that account for genotyping error
mhlist2 <- ... |
faba9f9dd635bb28e55b956544f88ab7a8b04945 | c9ebf93e5aa135373f5200b51f80016e9e8b0739 | /map_file.R | 69ae37bb305a4d2d648d77399abe2b56ba6b3934 | [] | no_license | humanpowered/COVID19Shiny | 3b82ddc61354f96627e28c080f09fc3d15115278 | eae98cecde423b60f159477d0b6510ab9042dd9d | refs/heads/master | 2022-11-10T23:03:06.498995 | 2020-06-29T22:09:57 | 2020-06-29T22:09:57 | 271,098,770 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,021 | r | map_file.R | state_maps <- readRDS('C:/Users/craig/OneDrive/Documents/R Projects/COVID19Shiny/COVID_Tracker_1.0/state_maps.rds')
nation_map <- readRDS('C:/Users/craig/OneDrive/Documents/R Projects/COVID19Shiny/COVID_Tracker_1.0/nation_map.rds')
ca_counties_map <- readRDS('C:/Users/craig/OneDrive/Documents/R Projects/COVID19Shiny/CO... |
4e8ae26af263bfd70b318bf0f25d4573c05c69e4 | 3c4550342213168a849defab116cb734bf35cd50 | /code/reference/summaries_JT.R | 5a6cecaca0505cbf0132e32505202c5a104f4ab3 | [] | no_license | guizar/Pest-MS | b8eaaaa8acb9390f6947624fa0dcdf6c031dbd37 | 95622943a8f23dd89215a49c82d37c5a500b4b8e | refs/heads/master | 2020-03-31T09:01:09.293619 | 2015-05-09T06:06:58 | 2015-05-09T06:06:58 | 28,886,343 | 0 | 1 | null | 2015-01-14T23:12:01 | 2015-01-06T22:20:53 | R | UTF-8 | R | false | false | 41,715 | r | summaries_JT.R | # summary tables ----------------------------------------------------------
setwd("~/Dropbox/climate change/food security/climate and crop pressure MS/data/ascii_crops_hires")
C_TO_R<-data.frame(read.csv("COUNTRY_TO_REGION.csv", header=TRUE))
# now just need to use plyr and ddply to aggregate by region and subregi... |
8b43ac48b23af06c468849a88a5a808032f7cd99 | 6ee38ee6cfe82f0385330c9f27c148fdad82ca1d | /Tableau/IBRD Loan/Data Preprocessing.R | 7e904cceab9999c0314c8410268b4c4da22da8c4 | [] | no_license | NitinNandeshwar/Cork-Institute-of-Technology | 4f0aeeb78bf26e4cc65e17163c90b9791af3e45a | 88c0efc6da1c5dd948a69d73a09a584e7d179c02 | refs/heads/master | 2020-12-27T06:36:13.387901 | 2020-11-05T18:16:59 | 2020-11-05T18:16:59 | 237,798,098 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,431 | r | Data Preprocessing.R | ################################################################
################################################################
### ###
### DATA INPUT AND Preprocessing ###
### ... |
083bf9d57ef27b3293858abeabfc85c23f9584b9 | 6e4f004782186082b73025cda95f31bcae76afcf | /man/gl.assign.Rd | ba22d853915485ef2ad110e3ee5e640adaec8154 | [] | no_license | carlopacioni/dartR | 319fbff40a385ca74ab7490b07857b0b027c93a8 | 06614b3a328329d00ae836b27616227152360473 | refs/heads/master | 2023-08-23T00:32:10.850006 | 2021-09-08T06:52:44 | 2021-09-08T06:52:44 | 262,468,788 | 0 | 0 | null | 2020-05-09T02:07:08 | 2020-05-09T02:07:07 | null | UTF-8 | R | false | true | 4,253 | rd | gl.assign.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gl.assign.r
\name{gl.assign}
\alias{gl.assign}
\title{Assign an individual of unknown provenance to population}
\usage{
gl.assign(
x,
unknown,
nmin = 10,
dim = NULL,
alpha = 0.05,
threshold = 0,
verbose = 3
)
}
\arguments{
\item... |
d0fb4e895f5633a67060d09b2fd57bb9e24cfacb | a3c78700a65f10714471a0d307ab984e8a71644d | /models/stics/man/model2netcdf.STICS.Rd | 7fc4ce7524aca139b62c83da27566c720e6e8564 | [
"NCSA",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | PecanProject/pecan | e42a8a6a0fc9c0bb624e0743ab891f6cf131ed3f | ce327b92bf14498fa32fcf4ef500a7a5db5c9c6c | refs/heads/develop | 2023-08-31T23:30:32.388665 | 2023-08-28T13:53:32 | 2023-08-28T13:53:32 | 6,857,384 | 187 | 217 | NOASSERTION | 2023-09-14T01:40:24 | 2012-11-25T23:48:26 | R | UTF-8 | R | false | true | 728 | rd | model2netcdf.STICS.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/model2netcdf.STICS.R
\name{model2netcdf.STICS}
\alias{model2netcdf.STICS}
\title{Code to convert STICS' output into netCDF format}
\usage{
model2netcdf.STICS(
outdir,
sitelat,
sitelon,
start_date,
end_date,
overwrite = FALSE
)
}
\... |
b936110458234ae71850c8d0673ba02b3d66de47 | dac4a8f2b14dbb92dd07e9ca9642410ae407a2f2 | /man/event1s.df.Rd | d6d77c85afd485c0d32df975661f5fd2cf13bc8c | [] | no_license | dstgithub/GrpString | 0710f0b5d1e8a90ee1e94e5a2f6facb19bc48c97 | 45b4da9cc59c71ddb8b53d7b6753665b7ff960fe | refs/heads/master | 2021-01-12T03:26:45.555515 | 2017-11-15T21:40:25 | 2017-11-15T21:40:25 | 78,210,123 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 469 | rd | event1s.df.Rd | \name{event1s.df}
\alias{event1s.df}
\docType{data}
\title{
Data frame containing event names
}
\description{
A data frame containing event names, There are 45 rows.
Each row has 26 event names.
}
\usage{data(event1s.df)}
\format{
A data frame with 45 observations or rows.
}
\note{
The event names are ... |
90556f6a13a58393a7a5dda31349ca1785dd767f | 189a7cf9828675253d12d941a80623c137ecc74f | /man/createLabtestDataFrame.Rd | fc90d7519d6bafa4b9afef07c50ace80795959f5 | [] | no_license | OHDSI/Cert | 773415562764f9aa1fff9dd944810539ebb18cdd | f1584475686b9664e9e0d086cc365218ab4e4921 | refs/heads/master | 2020-04-16T19:41:52.600806 | 2016-08-30T06:06:44 | 2016-08-30T06:06:44 | 36,716,779 | 3 | 2 | null | null | null | null | UTF-8 | R | false | true | 531 | rd | createLabtestDataFrame.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cert.R
\name{createLabtestDataFrame}
\alias{createLabtestDataFrame}
\title{Create data frame for a laboratory test information}
\usage{
createLabtestDataFrame(id, name, type)
}
\arguments{
\item{id}{OMOP CONCEPT ID of laboratory test}
\item{... |
68217ab6827d593dacc3a1b8afff3f0eddbd821e | e646416a1bbc302f73d2fdcbe78c5a8069e40fc8 | /metacommunity/mc_dit.R | 59a9e3cbbaaed88854be50190e905f25389087b5 | [
"MIT"
] | permissive | jusinowicz/info_theory_eco | c0ef0c0f94eca2df3b7308098f05b72233261c43 | b0770b10464732aa32d13f46ba3c5ef958a74dcc | refs/heads/master | 2022-05-28T19:34:50.642858 | 2022-05-05T17:37:19 | 2022-05-05T17:37:19 | 140,295,569 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,020 | r | mc_dit.R | #=============================================================================
#Load libraries
#=============================================================================
library(tidyverse)
library(RandomFields)
library(vegan)
#Patrick Thompson's metacommunity model functions:
source("./mcomsimr-master/R/MC_simula... |
463908a84bdbfdad6e8b5c70e8dd31b04bd882ec | b700538ed9715b7a0e208097d07d044dd84e6e02 | /R4CouchDB/man/cdbAddAttachment.Rd | ec1112587d15caaf451a1d6457399d7bc6d9d80f | [] | no_license | lmilev/R4CouchDB | 75849f83e61fc8d74bd2120c2188fffde7b8cca4 | e5450d23ca2187c1fc4cfb27714daa31ab5c4781 | refs/heads/master | 2021-01-24T09:57:20.211744 | 2017-03-05T16:26:12 | 2017-03-05T16:26:12 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,542 | rd | cdbAddAttachment.Rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/cdbAddAttachment.R
\name{cdbAddAttachment}
\alias{cdbAddAttachment}
\title{Add attachments}
\usage{
cdbAddAttachment(cdb)
}
\arguments{
\item{cdb}{The list \code{cdb} has to contain
\code{cdb$fileName},\code{cdb$serverName}, \code{cdb... |
f06d8bdb26397fcaf26b117eda506f8a584c9ad7 | 714287e4d7253d7ae41c2e178bf405e06cee7587 | /oishi.week3.R | cf3f67abf6ff192be1d38dcc66e935fde71cf677 | [] | no_license | tfoishi/com521_tanya | 7186a64ab40387d524a42d82ede9fe64b6420dc9 | 55fa22b5ba9b8abfe4170267aa1d2c4081624fd5 | refs/heads/master | 2021-04-29T06:20:04.481754 | 2017-02-21T23:07:10 | 2017-02-21T23:07:10 | 77,967,777 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,379 | r | oishi.week3.R | #PC 4
#Next time do more notes.
summary(week3_dataset.tanya)
ncol(week3_dataset.tanya)
nrow(week3_dataset.tanya)
sd(week3_dataset.tanya$x)
sd(week3_dataset.tanya$y)
var(week3_dataset.tanya$x)
var(week3_dataset.tanya$y)
hist(week3_dataset.tanya$x)
hist(week3_dataset.tanya$j)
hist(week3_dataset.tanya$i)
hist(week3_dat... |
f5af84c6ad088d88f2ae35663711765b8d621808 | 01e6f98609708ebdfd6d1db5fda9cb443f9f7856 | /man/year-day-arithmetic.Rd | 68500ad98376cd4963c59c7f7b3fa75ddcc8b779 | [
"MIT"
] | permissive | isabella232/clock-2 | 3258459fe4fc5697ce4fb8b54d773c5d17cd4a71 | 1770a69af374bd654438a1d2fa8bdad3b6a479e4 | refs/heads/master | 2023-07-18T16:09:11.571297 | 2021-07-22T19:18:14 | 2021-07-22T19:18:14 | 404,323,315 | 0 | 0 | NOASSERTION | 2021-09-08T13:28:17 | 2021-09-08T11:34:49 | null | UTF-8 | R | false | true | 1,777 | rd | year-day-arithmetic.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gregorian-year-day.R
\name{year-day-arithmetic}
\alias{year-day-arithmetic}
\alias{add_years.clock_year_day}
\title{Arithmetic: year-day}
\usage{
\method{add_years}{clock_year_day}(x, n, ...)
}
\arguments{
\item{x}{\verb{[clock_year_day]}
A ... |
2512487df8adfe4810509d585800d8feabb42d42 | 07283623f9530c8c1ac7408eb099059d6deb7919 | /man/salvage_model.Rd | caab4724f2eabc1a5e5ef56ee763740afc97e6b8 | [] | no_license | hinkelman/DSM2Analysis | 75314f00a8a0a0723d0f43813558148b29c80035 | ebbe09bb57f504b6e1acb8f2939d5491b1abae4a | refs/heads/master | 2023-04-30T16:50:14.140023 | 2021-05-12T20:12:59 | 2021-05-12T20:12:59 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 365 | rd | salvage_model.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/salvage_model.R
\name{salvage_model}
\alias{salvage_model}
\title{Salvage model}
\usage{
salvage_model(facility)
}
\arguments{
\item{facility}{Water export facility: CVP, SWP, both}
}
\description{
Zero-inflated model of salvage as function o... |
ce0bbdc4ec3190d1669781f6b61c1e4a094ac151 | 8ecb53df18a2d1a3975368baaa892a5fc01086f8 | /general_analysis.R | 8d0f5525546a5f337fffc57ef7bf840b0274e20b | [] | no_license | AndersenLab/CrossSim | 1a39f48e18e447eed296b5587f51b4ce6d06d4b5 | 7d8f47107004f40d8bd1cd32450bb6188c5f41f9 | refs/heads/master | 2021-01-20T16:55:08.556304 | 2015-06-11T19:01:48 | 2015-06-11T19:01:48 | 16,160,349 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 251 | r | general_analysis.R | data <- read.csv(file = "~/GitHub/CrossSim/general_statistics_1000_1.csv", header = TRUE, sep = ',')
data <- data[order(data$Number.of.Back.Crosses), ]
qplot(data$Number.of.Back.Crosses, data$Percent.Selected.Chromosome, data = data, geom = "jitter")
|
3b7ed817b6b61bc05840e8d9ced852867ddab8ff | b47aa2e09add49ab85ec3b04c3e3279f28706c1c | /man/tailindexplot.Rd | e8459440ce7f71a668b070ba4f46d0469da35d3e | [] | no_license | ceesfdevalk/EVTools | db232bc94b0a22b1a0fdfbd8ba5e6e9e94e8ad3c | 0e3440f031b6a8abcfd6fc00d981d0656710d93e | refs/heads/master | 2022-09-30T06:25:51.784236 | 2022-08-22T07:48:01 | 2022-08-22T07:48:01 | 130,972,770 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 754 | rd | tailindexplot.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tailindexplot.R
\name{tailindexplot}
\alias{tailindexplot}
\title{tailindexplot}
\usage{
tailindexplot(es, params)
}
\arguments{
\item{es}{list containing tail estimates from a single sample}
\item{params}{(optional) list (see below)}
}
\val... |
0b046eea5866b1a941f8efe98511f8b6469e23b4 | 07a42f5c19d8007013051d1f825d5d782249494b | /R/Mooran.R | 408a6247def9a457976d0a9afd061305c2e0bf3f | [] | no_license | jcms2665/WorkshopR_3 | b5267858e91c11c6020a6beb42bbda014b9daa38 | 57559b55956e0a6cebe22042d2c73a7878896ea1 | refs/heads/master | 2021-04-30T01:00:19.736606 | 2018-02-14T08:39:54 | 2018-02-14T08:39:54 | 121,471,750 | 0 | 0 | null | null | null | null | ISO-8859-1 | R | false | false | 4,724 | r | Mooran.R |
library(rgdal)
library(sp)
library(GISTools)
library(RColorBrewer)
library(ggplot2)
library(reshape2)
library(grid)
library(gridExtra)
library(foreign)
library(spdep)
# Lista de librerías:
list.of.packages <- c("rgdal", "sp", "GISTools", "RColorBrewer", "ggplot2",
"reshape2", "... |
996b984b849cfa3064af028feecb1d2732901762 | 93948587ecb19bd226dd7c6b499f90a5ae3c472e | /R/canClu.R | 99682d1a3897a53536d360b6b8714521877c80ef | [] | no_license | cran/blockmodeling | 2aee1677bc94cd7daf7b48f5a7b7a662100a648e | f1766c756496c05040f8a8015f31036f13224659 | refs/heads/master | 2022-12-01T06:35:33.586891 | 2022-11-22T11:30:02 | 2022-11-22T11:30:02 | 17,694,825 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,564 | r | canClu.R | #' @encoding UTF-8
#' @title Create canonical partition and find unique canonical partitions in a list of partitions.
#'
#' @description
#' It is used to convert any partition to a canonical partition. A canonical partition is a partition where the first unit is in cluster 1, the next unit that is not in cluster 1... |
cbe1ec0c377891aafcf76bd5d4329d228622f7eb | e59105c4b262f1203231f5ea05c87c1d922eea81 | /manuscript/code/eu_o3.R | 7b6b15225223a4aa456910a5907e9285903b388b | [] | no_license | RedCobbler/business_intelligence_with_r | d869050a9c8c63c66cdbd391d025845c45f1625d | fad45dc881d23108764f2a02a68b629d0ff6f02c | refs/heads/master | 2021-01-12T00:39:57.191026 | 2016-09-28T21:06:38 | 2016-09-28T21:06:38 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,465 | r | eu_o3.R | # Code used to set up Ozone Pollution in EU
# Chapter 7 Mapping section
# Net result is eu_o3.csv in this directory
# Data requires manual download from
# http://www.eea.europa.eu/data-and-maps/data/airbase-the-european-air-quality-database-8
# Download both the stations and the statistics zip files
o3stations = re... |
80d3e1327783e6d53f1b1bff61c7d2cc824e4ef5 | 67c4efb56a9a6611325ac89d2914a7467fa378c0 | /R/discard.R | c0647c2d325547e184006bf73ebef0641fb23a59 | [] | no_license | rpahl/container | 0e197616a12bd0daff0d38c38740ab404dea7cde | e14d3c027c364de02be8198a7d3cc382577bf865 | refs/heads/master | 2022-12-06T09:05:31.094044 | 2022-12-05T15:27:44 | 2022-12-05T15:27:44 | 124,919,709 | 18 | 2 | null | 2022-12-05T15:57:48 | 2018-03-12T16:37:36 | R | UTF-8 | R | false | false | 1,269 | r | discard.R | #' Discard Container Elements
#'
#' Search and remove an element from an object. If the element is not found,
#' ignore the attempt.
#' @param .x any `R` object.
#' @param ... elements to be discarded.
#' @export
discard <- function(.x, ...) UseMethod("discard")
#' @rdname discard
#' @export
ref_discard <- function(.x... |
e0cc49be9a2df93646fad6d737f499109ed578d6 | 7dc56416fcc41def35bae8065ece00f89421a608 | /man/dcleaner.Rd | ac78b6951bb0a69520da763e3cafff6b26774784 | [] | no_license | Muscade/dcleaner | bc9f65eef1cf62315c92099ff4b51ed055021226 | 6a66040ec804a0b4ce29b21758f72774c7ca4536 | refs/heads/master | 2020-12-26T12:52:38.054351 | 2020-02-02T20:45:51 | 2020-02-02T20:45:51 | 237,514,834 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 480 | rd | dcleaner.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dcleaner.R
\docType{package}
\name{dcleaner}
\alias{dcleaner}
\title{dcleaner: A package for cleanning and mungling data, importing and exporting data to DB.}
\description{
The dcleaner package provides three categories of important functions... |
861959ef7240187d923a480bd35f3d17bb164d2e | 7cb268fcda08de51d8cdcf224f0d204e5fcbda22 | /differential_expression/differential.expression.ages.resampled.pc.lncRNA.R | c8d5a0c837a560aa312b23fbd19a8fdb022929c0 | [] | no_license | anecsulea/LncEvoDevo | 2fa8169c06875675166521ce44fe270225b2dd1d | 5b22ccdc4e280c02bd58352cfd9f23b9cb69c44a | refs/heads/master | 2020-06-01T07:51:34.135059 | 2019-06-30T17:48:19 | 2019-06-30T17:48:19 | 190,705,719 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,625 | r | differential.expression.ages.resampled.pc.lncRNA.R | ########################################################################
path="LncEvoDevo/"
pathResults=paste(path, "results/differential_expression/", sep="")
########################################################################
set.seed(19)
options(stringsAsFactors=F)
library(DESeq2)
########################... |
22e37a3026013373619d6207e632f211a0ec33a4 | b5e4d4f4c36d574393ab069e568d83885e61e1ca | /R/genPoints.R | 6ae94a680de14977b50049ae5286f27d2563fcc8 | [] | no_license | robiRagan/voteR | 9ed860de34e167d1ff0bc89c3e47962cd4cc064e | c20de1f2f8fcffe928d97e29d939a3cf272ba948 | refs/heads/master | 2020-12-24T15:40:49.572281 | 2020-02-20T15:46:13 | 2020-02-20T15:46:13 | 155,420,318 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,459 | r | genPoints.R | #' genPoints
#' Generates one or two dimensional points.
#'
#' Generates one or two dimensional points from one of distributions in base R.
#' The user can set up bounds on the dimensions. If bounds are set then genPoints()
#' will discard any points outside the bounds and resample.
#'
#' Note that if the user cho... |
114f956ff082ba51c16d47ded4e7f9f1d9bc274a | 38d166ede31183e2121388be0f66fe9d7ac4e93a | /man/get_max_taxonomic_rank.Rd | 7f0b0a6e1bf5dbba3861dccc53802a732fa7e31d | [
"MIT"
] | permissive | vmikk/metagMisc | a01151347b620745b278265700e503dc74669af5 | 310b1a40951de46348084e150d7471ed66feb0c8 | refs/heads/master | 2023-08-31T08:41:27.684905 | 2023-08-28T10:09:50 | 2023-08-28T10:09:50 | 76,531,351 | 38 | 12 | MIT | 2019-07-29T06:12:12 | 2016-12-15T06:40:05 | R | UTF-8 | R | false | true | 1,335 | rd | get_max_taxonomic_rank.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_max_taxonomic_rank.R
\name{get_max_taxonomic_rank}
\alias{get_max_taxonomic_rank}
\title{Determine the lowest level of taxonomic classification}
\usage{
get_max_taxonomic_rank(x, return_rank_only = FALSE)
}
\arguments{
\item{x}{Either a p... |
a09bdd9bea7cadac6e04f877d52734d2b0656948 | fc8014537f843be228bc5808cc379b66dc75be94 | /man/Daniels_2020C.Rd | 4c1558b69dd944d361764d141b633147c89f6511 | [
"MIT"
] | permissive | mrc-ide/SIMPLEGEN | db09a91438b788853ec24541f73dc516fc07f4b0 | a8500cecb0345f16b36226aa4c5b386f397d7981 | refs/heads/master | 2023-04-14T16:55:50.814805 | 2023-03-30T16:23:49 | 2023-03-30T16:23:49 | 186,381,846 | 13 | 1 | MIT | 2023-03-30T16:23:51 | 2019-05-13T08:51:43 | R | UTF-8 | R | false | true | 1,705 | rd | Daniels_2020C.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{Daniels_2020C}
\alias{Daniels_2020C}
\title{24-SNP barcode data from Richard Toll, Senegal (Daniels et al., 2020)}
\format{
A dataframe with 30 columns, giving sample ID and year (columns 1:2),
genomic data at 24... |
4390f4ecdd8d5814560fda226427f58e7376defc | 4455b3494711314fc826125fb0251b24de546c98 | /cytometry.R | 3745db45688d3cfd47cf69cfde7d8b11354158c9 | [] | no_license | hhhh5/HRS | 908d5c5248cd9f9c3198cb6f3a1deca48aa49158 | 3be07971e4008e17beaa00ee12cf726ebb907b1f | refs/heads/main | 2023-04-12T02:47:22.581679 | 2022-11-27T18:49:54 | 2022-11-27T18:49:54 | 345,698,965 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,884 | r | cytometry.R | # Flow cytometry measurements
flow = '/nfs/turbo/bakulski1/Datasets/HRS/jonheiss/sensitive/flow/hrsflowdata2016.sas7bdat'
vbs = '/nfs/turbo/bakulski1/Datasets/HRS/jonheiss/sensitive/flow/hrs2016vbs.sas7bdat'
xwalk = '/nfs/turbo/bakulski1/Datasets/HRS/jonheiss/sensitive/flow/xwalk.csv'
flow %<>% read_sas %>% as.da... |
601454029fec0159fdf945c65f09a486f2926527 | 35e702005356610d62e60fcf11efdaaca770398e | /gt:dp.dup.R | 84e6d709d8807445b0a9987a5fcf86efe9340ae4 | [] | no_license | jingg46/Research-oral-cleft | 744d1a23ca59f4aec4acacd8eaf52961b49e8f83 | db42552e66cad11ec3cebb220858800a866507fb | refs/heads/master | 2020-03-11T03:38:46.903604 | 2018-07-21T18:29:59 | 2018-07-21T18:29:59 | 129,754,234 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 15,132 | r | gt:dp.dup.R | library(VariantAnnotation)
##target sequencing data
target <- readVcf("/users/jli/target.dup.vcf", "hg19")
target.gt <- geno(target)$GT
target.gt <- as.data.frame(target.gt, stringsAsFactors = F)
target.gt[target.gt == "."] <- NA
gmkf <- readVcf("/users/jli/gmkf.dup.vcf", "hg19")
gmkf.gt <- geno(gmkf)$GT
gmkf.gt <- ... |
162739b10b0bb361c3daeb160d3f41b2cb8d4f1d | 6112802e8e27d4550c851c06fd39a1091e77e71a | /ProjectEuler/problem002.R | 59fb6d12cbca9729262c5ce2f5a47cce9317dc6f | [] | no_license | jlopezsi/r.prevos.net | f4e2e79f208cf913cc721178be4e9d1e4bc4e6e9 | 5b21be9b8b2f5a19d32506f06fca3bcba2829a18 | refs/heads/master | 2020-03-15T10:31:21.442805 | 2018-04-17T01:15:14 | 2018-04-17T01:15:14 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 664 | r | problem002.R | # Problem 2: Even Fibonacci numbers
# https://projecteuler.net/problem=2
# By considering the terms in the Fibonacci sequence whose values do not exceed four million, find the sum of the even-valued terms.
# http://r.prevos.net/euler-problem-2/
fib <- c(1, 2) #Define first two numbers
while (max(fib) < 4E+06) {
... |
e4bd3e4995f141450491bd6c27a412961bacbe10 | ee503bac3ea764666106b3eff49406903f066d7d | /R/compute_hydat_peak_frequencies.R | 9a51bbadc1aae8db77e2a04683a784bc32e749e6 | [
"Apache-2.0"
] | permissive | bcgov/fasstr | a90a88702543084c7d36c7f7386745d4c24672b7 | 10da0bb28e2f55d0b9c2b71de8b028f5a4071c21 | refs/heads/main | 2023-04-02T17:38:35.947960 | 2023-03-22T20:25:08 | 2023-03-22T20:25:08 | 108,884,386 | 61 | 14 | Apache-2.0 | 2023-03-22T20:26:18 | 2017-10-30T17:23:30 | R | UTF-8 | R | false | false | 8,323 | r | compute_hydat_peak_frequencies.R | # Copyright 2019 Province of British Columbia
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
0ab86c9e14508212c8028d3c7ec88970f2b69351 | 65396ca6147fbb0dbed9c8bdf9c7671afb8dc210 | /sbs_bayes/Untitled.R | e85c378743f99c180fc95a0fba6d6c7d3ae0eb01 | [
"MIT"
] | permissive | elahi/sbs_analysis | 587f4352389cc7b208ffd1fd5b241137203bb25b | a3c05a84d4e74a6a6e6d9fd9a6d1bc8211748c91 | refs/heads/master | 2021-01-17T12:09:45.289489 | 2019-11-15T04:23:03 | 2019-11-15T04:23:03 | 39,157,467 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,605 | r | Untitled.R | # Set-up the data generating mechainsm
set.seed(666)
N <- 500
x <- runif(N, max=10)
alpha <- 1
beta <- 2
y <- alpha + beta * x + rnorm(N, sd = .6 * x)
p <- 0.95
# The dataset to be used for estiamtion
data_set <- list(y = y, x = x, p = p)
data_frame <- as.data.frame(data_set)[-3]
jags_code <- "
... |
ba7775242e8cced3e1ad8a29aa19e6cb8864a960 | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /cran/paws.mobile/man/devicefarm_create_upload.Rd | 399c1727802f8cfa107647d4203edfe086bf7b46 | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | true | 4,716 | rd | devicefarm_create_upload.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/devicefarm_operations.R
\name{devicefarm_create_upload}
\alias{devicefarm_create_upload}
\title{Uploads an app or test scripts}
\usage{
devicefarm_create_upload(projectArn, name, type, contentType)
}
\arguments{
\item{projectArn}{[required] T... |
8834bcfac0aa07144eaacb3138781825ee72e27c | 6a28ba69be875841ddc9e71ca6af5956110efcb2 | /Schaum'S_Outline_Series_-_Theory_And_Problems_Of_Statistics_by_Murray_R._Spiegel/CH4/EX4.4.6/Ex4_4_6.R | 1eaf8804a67cece9375e1d23224d5c7f8f3fc956 | [] | permissive | FOSSEE/R_TBC_Uploads | 1ea929010b46babb1842b3efe0ed34be0deea3c0 | 8ab94daf80307aee399c246682cb79ccf6e9c282 | refs/heads/master | 2023-04-15T04:36:13.331525 | 2023-03-15T18:39:42 | 2023-03-15T18:39:42 | 212,745,783 | 0 | 3 | MIT | 2019-10-04T06:57:33 | 2019-10-04T05:57:19 | null | UTF-8 | R | false | false | 144 | r | Ex4_4_6.R | #PAGE=94
q1=65.5+(2*3)/42
q3=68.5+(10*3)/27
q=(q3-q1)/2
q2=(q3+q1)/2
q2=round(q2,2)
q=round(q,2)
cat(q2,'+',q,'kg')
cat(q2,'-',q,'kg')
|
98e5bfd15aa6e4eb2b35ec7f615e27f8d8f7721f | 7b73aadd5d76910a714e16ebfc31a27d2448aea2 | /cachematrix.R | 253e44fd2f37d06cef6a446cca968fcfb5a1e821 | [] | no_license | SUNILKUMARCHINNAMGARI/ProgrammingAssignment2 | e64baae9c32cb2b7932b455813b35c9d4c7bf3bc | 6883c67bb8cf6894003e3e905c4a788674fee23b | refs/heads/master | 2020-12-25T05:02:37.790457 | 2014-06-21T17:14:15 | 2014-06-21T17:14:15 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 855 | r | cachematrix.R | ## makeCacheMatrix creates a special matrix that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
matinv <<- solve(x)
set <- function(y) {
x <<- y
matinv <<- NULL
}
get <- function() x
setmatinv <- function(matinv) matinv <<- matinv
getmatinv <- function() matinv
list(set = set, ge... |
6ae36b63ae4b4cbb9bb31f10b07b87d1e4a0c139 | 880c8d4a9401d2e08b62a23306fe5b5f4dfeeb78 | /man/intersect_prices.Rd | b96bfd1db8e96f7d413f1699084f56711129453e | [
"MIT"
] | permissive | zumthor86/OptionsAnalytics | 6717ea8a76238f6a304171352e17e123db8dc088 | a1a9d56a0c635729b333086272d8f8d3c4e8642c | refs/heads/master | 2021-07-07T07:51:51.645454 | 2020-10-16T12:50:35 | 2020-10-16T12:50:35 | 196,432,023 | 8 | 5 | null | null | null | null | UTF-8 | R | false | true | 388 | rd | intersect_prices.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/intersect_prices.R
\name{intersect_prices}
\alias{intersect_prices}
\title{Return commmon time series}
\usage{
intersect_prices(prices)
}
\arguments{
\item{prices}{List of price dataframes}
}
\value{
Input dataframes with common time series t... |
de311a9d097e2415ce30cc64b3a367750d19ccf0 | 5227e8fb4619e3b4212613f3f779df8b7c3706b2 | /man/fake.phenos.Rd | 206bc147588bcac30c3a502a4c20dfacde29b48f | [] | no_license | phamasaur/qtlpvl | 5a5b930b4f12d67c7cc00840a63e9725da3dbc2b | 9c199f47c21a8deb5a50cda5c8b5423c49efa15c | refs/heads/master | 2023-04-19T05:30:01.716383 | 2015-08-26T05:32:19 | 2015-08-26T05:32:19 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,222 | rd | fake.phenos.Rd | % Generated by roxygen2 (4.1.1.9000): do not edit by hand
% Please edit documentation in R/qtlpvl-package.R
\docType{data}
\name{fake.phenos}
\alias{fake.phenos}
\title{Simulated Small Gene Expression Data Set}
\format{A matrix with 120 individuals in rows, 10 traits in columns.}
\description{
Simulated gene expression... |
596db34a6c5de08bf7220ad7c3ec5bb32d1665eb | f090937cedacfd819294faa2224cb3c8f24737f3 | /R/dotplot.R | f7d49767c312e57ea5ccabc9e0b3987b84fb37dd | [] | no_license | vitkl/DOSE | 1334bfa29e7eeba322550232c98d75d39b8d1707 | 9c09b0928f6d31014733d3248b6a638b07b604a8 | refs/heads/master | 2021-01-20T13:17:45.418994 | 2017-05-08T09:18:54 | 2017-05-08T09:18:54 | 90,470,418 | 0 | 0 | null | 2017-05-06T14:57:30 | 2017-05-06T14:57:29 | null | UTF-8 | R | false | false | 1,991 | r | dotplot.R | ##' @importFrom ggplot2 fortify
##' @importFrom ggplot2 ggplot
##' @importFrom ggplot2 aes_string
##' @importFrom ggplot2 geom_point
##' @importFrom ggplot2 scale_color_gradient
##' @importFrom ggplot2 xlab
##' @importFrom ggplot2 ylab
##' @importFrom ggplot2 ggtitle
##' @author Guangchuang Yu, Vitalii Kleshchevnikov m... |
4689da920998233ce8b0f9337aeec53dce26b2ec | 7f6a97022dfd69ee3c166d4fa2915ff70dd38ae2 | /R/Rkoder/unrate/lasso_generaliseringer/lars/lasso/bic/covtest.R | dc9fa504f69ebd05a65715651bb1ebd2ebc13022 | [] | no_license | TrineGraff/p10 | 1fc59edab01c802721a5c730ecfa7c08be9e86e5 | a6c3088af873507af4824f52a1e73c5c6e5c172e | refs/heads/master | 2021-04-30T14:39:44.881380 | 2018-06-20T08:51:04 | 2018-06-20T08:51:04 | 121,222,378 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 303 | r | covtest.R | source("shrinkage_metoder/lars/lasso/bic/insample.R")
covTest(lasso_fit, x_train, y_train)
which(coef(lasso_fit, s = lasso_bic$f_hat, mode = "fraction")!=0)
#variablerne 21, 35, 31,32,19, 79 tilføjes og fjernes igen
colnames(x_train)[79]
#variablen 78 bliver tilføjet, fjernet og tilføjet igen. |
bb497267ae3420255758b4d341b441453fe2b0ea | b844a7aa7d03d64383931bf0b1dce19888e55e33 | /11dtametadata/detecterror.R | 5d21f0dd4d2c8718c5ab97cad49246a0828d65d9 | [
"MIT"
] | permissive | mephas/datasets | 0c5d99944ac0eeac67b3c7c6d432dc424394a615 | f89d3511efe7efe2f96a1fe45ac9644247055ebf | refs/heads/master | 2023-01-04T09:28:11.020770 | 2022-12-23T08:32:43 | 2022-12-23T08:32:43 | 231,333,695 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 254 | r | detecterror.R | data <- read.csv("anti-ccp.csv")
library(dtametasa)
sapply(seq(1,0.1,-0.2), function(p)
{
fit <- try(dtametasa.rc(data, p=p))
if(inherits(fit, "try-error")) par <- rep(NA,5) else
fit$par
}
)
|
685f079f8e67924bd9671b3f4072c5d34c390164 | 818eaa5d5a84d25a61f16e9567b82d80344984aa | /presentation_times/presentation_times.R | e8a68688a28bf3d98cfce8cd17811de322e55879 | [] | no_license | justone/r | 6c7157774aa55a80c9352162b92c3cd1d685116c | 5ed460ed95fb9bd650090d1cf59581e75796a49d | refs/heads/master | 2021-01-10T18:30:16.596262 | 2012-05-11T03:45:42 | 2012-05-11T03:45:42 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,919 | r | presentation_times.R | #!/usr/bin/env Rscript
# for melt
library("reshape")
# for pretty plotting
library("ggplot2")
# for help with date labels and scaling
library("scales")
# Read in raw times
times.raw <- read.csv('decimal_times.csv')
# make a copy to clean up
times.clean <- times.raw
# make rownames first column
rownames(times.clean)... |
868bc5650d7f704955c24f05679210f0e7aa3c09 | ac8ba549475fe7caa6cc414b64c48bbc8c78dbdb | /chapter5/chapter5_resampling_lab.R | 28d0f1a090fbaf67a85f96e4141d5169154f3d7c | [] | no_license | Stochastic-Squirrel/ISLR_notes | 5c2f1eec0b71b258e491c929e8ff7e0e141a07dc | 3044dcffca23aba2077ff4f727bad339e2f9e843 | refs/heads/master | 2021-09-12T11:06:23.026588 | 2018-04-16T08:18:06 | 2018-04-16T08:18:06 | 113,603,277 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,203 | r | chapter5_resampling_lab.R | library(tidyverse)
library(ISLR)
library(boot)
set.seed(1)
#THE VALIDATION SET APPROACH
#sample without replacement from numbers 1:392
train <- sample(392,196)
lm_model <- lm(mpg~horsepower, data = Auto , subset = train)
#Calculate MSE = average of (Actual - predicted)^2
mse_lm_model <- (Auto[-train,"mpg"] - predic... |
9c80b288460a4be4626bbc581d1a8aa0198c035e | c410e65345f0c2d4cc6b68cdcac433696c887e97 | /regression_curv.R | 71a0551a4ff1bc5c0fed0d10b93b7b52fdad1d18 | [] | no_license | bgorillaz/Capstone | 033467ef312048f8466aeb774373a2986c94f978 | 7b027a8875620f28c3e877d3c21fbe42436610b0 | refs/heads/master | 2023-01-22T12:29:14.955985 | 2020-12-08T02:54:11 | 2020-12-08T02:54:11 | 319,498,335 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,528 | r | regression_curv.R | #load packages
library(data.table)
library(pscl)
library(MASS)
library(ndot.tools)
#set dir
setwd("/Users/ryanloos/Capstone/")
#load data
curv <- fread("clean_data/curv_for_model.csv")
#refactorize columns...
for(var in colnames(curv)) {
if (class(curv[[var]]) == "character") {
curv[[var]] <- as.factor(curv[[va... |
b26632445aebf06497ecaad22f5bd4671f366bf4 | 72d9009d19e92b721d5cc0e8f8045e1145921130 | /sdetorus/man/periodicTrapRule1D.Rd | eda0348a76d59b70d3dcfc810b260da3d3536a23 | [] | no_license | akhikolla/TestedPackages-NoIssues | be46c49c0836b3f0cf60e247087089868adf7a62 | eb8d498cc132def615c090941bc172e17fdce267 | refs/heads/master | 2023-03-01T09:10:17.227119 | 2021-01-25T19:44:44 | 2021-01-25T19:44:44 | 332,027,727 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 3,358 | rd | periodicTrapRule1D.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/auxiliary.R
\name{periodicTrapRule1D}
\alias{periodicTrapRule1D}
\alias{periodicTrapRule2D}
\alias{periodicTrapRule3D}
\alias{integrateSimp1D}
\alias{integrateSimp2D}
\alias{integrateSimp3D}
\title{Quadrature rules in 1D, 2D and 3D}
\usage{
p... |
0ed3b7d919d1849bdfe73c2adf0abf9f8bc1f672 | a5e940b336f8d906d5e9b42eff22986bf1156cb3 | /ui.R | 8b63fac5c9b0c411fa83fd3489b4fdb99246f0f5 | [] | no_license | raulzr/compstat2016 | be1322db403a0d28f1d000738d211ffb390c9f40 | 7cc5c77fb99779bab700d35573b56dc465db1647 | refs/heads/master | 2021-06-09T05:25:54.267668 | 2016-12-15T23:46:23 | 2016-12-15T23:46:23 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 215 | r | ui.R |
library(shiny)
shinyUI(fluidPage(
tabsetPanel(
tabPanel("Uno", tarea1UI("A")),
tabPanel("Dos", tarea2UI("B")),
tabPanel("Cuatro", tarea4UI("C")),
tabPanel("Cinco", tarea5UI("D"))
)
)
)
|
57c78177afdc2c48db4fb711dd39ab73d490a4f7 | 6c8d711db1ada9398e5b36463476844ab0e9e553 | /R/make_diagram.R | 14ce01edc9274a621495ada56481fa150af794c9 | [] | no_license | wzbillings/flowdiagramr | 8ca658c702f1c88b56fcbf55d1936fcaa7ce12cd | e048801c384aeca859ed86cc916dd2a65712e47c | refs/heads/main | 2023-06-07T22:17:29.353419 | 2021-06-21T16:41:30 | 2021-06-21T16:41:30 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 15,536 | r | make_diagram.R | #' Make a ggplot2 model diagram.
#'
#' @description
#' `make_diagram()` generates a **ggplot2** object based on the data frames
#' made with \code{\link{prepare_diagram}}. The function only applies
#' aesthetics that are not associated with x, y locations. Colors, linetypes,
#' and other graphical options can be set by... |
980150a500e51d35e9205118fd195a04f7886452 | eaa300dce01424b7975c86fee975d1b5389f25f8 | /AccountingDiscount.R | df9edfa073289fa3d56f97044c1dcfcf7207f57d | [] | no_license | shineice/Py | 9a4e4a6f1721f04d1cc501d6a8f3254bcbfd43c3 | c23c24a4ebe9d7b0601e35495f9f39153a6b1fb4 | refs/heads/master | 2021-06-23T09:14:18.948316 | 2020-11-30T10:32:08 | 2020-11-30T10:32:08 | 163,953,206 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 8,679 | r | AccountingDiscount.R | rm(list=ls())
library(RODBC)
library(dplyr)
library(stringr)
library(readxl)
library(lubridate)
library(mailR)
m <- as.numeric(format(Sys.Date(), "%m"))
m=m-1
ddd=1
##get week data
channel <- odbcConnect("NetSuite", uid="yao.guan@top-line.com", pwd="NetYG@Davis")
discount<-sqlQuery(channel,paste0(
"select
ITEMS.Na... |
c895ac06b2073d7b933d8498a5e77ee34da2d8fe | 8d4b15ba1c6004e6e2f40b01de3543c61df72dd7 | /predict_validate.R | 64f2900834bd47d09cb0cfcccc990914daaccdd0 | [] | no_license | prashantg123/PMnPred | 4c4aba6b720e0a5e58fe30758f137b809252fc3e | 7558b32c91ed12a233a4cfa2ed48fe02d298237f | refs/heads/master | 2020-03-16T14:21:34.944811 | 2018-05-09T06:52:17 | 2018-05-09T06:52:17 | 132,714,288 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,984 | r | predict_validate.R | library(devtools)
load_all("d:/InfoTrie/global")
zz <- file("d:/InfoTrie/output/error.txt", open="wt")
sink(zz, type="message")
args <- commandArgs(TRUE)
input <- args[1]
params <- ReadParam(input)
write.csv(input, paste0(params$app.path,"/output/input.csv"))
data<- read.csv(params$file.name, header = TRUE)
value... |
8ed21c1d917e435e3c2730aa04f0bc3472b884e8 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/spacejam/examples/plot.SJ.Rd.R | ea5697414c0a7398b65ab2d044c5885c1073979c | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 532 | r | plot.SJ.Rd.R | library(spacejam)
### Name: plot.SJ
### Title: plot an object of class 'SJ' or 'SJ.dag'
### Aliases: plot.SJ plot.SJ.dag
### ** Examples
p <- 100 #variables
n <- 50 #observations
#Generate Data
set.seed(20)
g <- rdag(p,80)
data <- generate.dag.data(g,n,basesd=c(1,0.5,0.5))
X <- data$X
#Fit conditional independenc... |
fc6bdb284c99a0b756109fc65cdf11f5746eeeaa | 8541c4ed0784bf1d448131152f50f02c36c0dc0f | /exercicios_cap2.R | 22cdcc745cd268a800731b9b723e1864c190fc08 | [] | no_license | aglotero/ct-234 | 55638f76798ca3efca7a605aaa09b84c41edd8c5 | 464eae766307419a63be6c5190c514e7c3cb3865 | refs/heads/master | 2021-01-10T14:56:00.547217 | 2016-03-12T20:59:21 | 2016-03-12T20:59:21 | 53,752,849 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,673 | r | exercicios_cap2.R | naturaisCrescentes <- function(n){
if(n < 0)
{
return('')
}
naturaisCrescentes(n-1)
cat(paste0(n, ' '))
}
naturaisDecrescentes <- function(n){
cat(paste0(n, ' '))
if(n == 0)
{
return('')
}
naturaisDecrescentes(n-1)
}
maximoEmVetor <- function(vetor){
if(length(vetor) == 1){
... |
23f1cc8cd779d0c43d970c5f8a7935f4ead3189b | dec2677d31a0cfc6b2930700c0856ac84b19de32 | /doc/preprocessing.R | b47793cc163b9d6d973c7cf514dbe42322abd30b | [] | no_license | yvonnechanlove97/Multi-stage-Financial-Modeling-R | 41fea9e8c245bbe4f1dfd212f06817170ceda675 | 8052a8ec615941abe106f63dace23f9e78b683b5 | refs/heads/master | 2022-10-17T22:27:57.640942 | 2020-06-15T21:58:23 | 2020-06-15T21:58:23 | 271,899,407 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,771 | r | preprocessing.R | ## ----fig.width=7, fig.height=4, warning=F, message=F--------------------------
library(FinancialModelingR)
library(png)
library(grid)
img <- readPNG("private_data/july2020.PNG")
grid.raster(img)
## -----------------------------------------------------------------------------
contractsForJuly2020 <- FinancialModeling... |
46901511f43553ae1c48b0c5bc6e9cbb3200e0ea | 92e240738a4ccf673b9f3610386eaa08eef26d6f | /momentum/rebal-frequency/combine.R | 2dd312f752e20ebba38fbe0aa64d17fdec2037b3 | [] | no_license | stockviz/blog | 564a4671202b92a2d63f13f0207fd8a35810c0b6 | e00c055742a1229c612669ee29d846a6e2475a43 | refs/heads/master | 2023-09-01T15:59:07.746886 | 2023-08-31T04:01:37 | 2023-08-31T04:01:37 | 138,372,618 | 12 | 4 | null | null | null | null | UTF-8 | R | false | false | 1,072 | r | combine.R | library('quantmod')
library('PerformanceAnalytics')
library('PortfolioAnalytics')
library('tidyverse')
library('lubridate')
options("scipen"=100)
options(stringsAsFactors = FALSE)
source("D:/StockViz/public/blog/common/plot.common.R")
reportPath <- "."
load(sprintf("%s/symRets.Rdata", reportPath)) #symRets
symRe... |
5b7ddc284a6e512c1ac082e957603e5685dafabb | 4e7044d8987736ca8e639f8467e4011cb57a7c54 | /WP6/CLEFRDB/R/class1Trip.R | 1c567dd395c8c0e97032687c23f4e62c59bc60c0 | [
"MIT"
] | permissive | ices-tools-dev/FishPi2 | 16ab67c7883e909f896dbca8ed0145f0a1765f35 | d2818819f053a66008a4a94aa896c5777e17f1db | refs/heads/master | 2020-05-22T15:23:06.977219 | 2019-08-29T22:55:34 | 2019-08-29T22:55:34 | 186,406,874 | 4 | 2 | null | null | null | null | UTF-8 | R | false | false | 4,391 | r | class1Trip.R | #' validity Trip method
#'
#' @param object a time object
#'
validTrip<-function(object){
#Triptype<-NULL
#utils::data(Triptype,package="fishpi2qc")
#print(Triptype)
check<-TRUE
#data length
#if(F){
#object<-new("Trip")
nomslot<-methods::slotNames(object)
lengthall<-c()
for(i in nomslot){
len0<-length(... |
05559f74a3974cd6ac9f4b2cf3150dac91249e9f | 29585dff702209dd446c0ab52ceea046c58e384e | /DJL/R/map.soa.sf.R | c32fd835c8fb4ffdfc66def7523dc092f66bfc81 | [] | no_license | ingted/R-Examples | 825440ce468ce608c4d73e2af4c0a0213b81c0fe | d0917dbaf698cb8bc0789db0c3ab07453016eab9 | refs/heads/master | 2020-04-14T12:29:22.336088 | 2016-07-21T14:01:14 | 2016-07-21T14:01:14 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,208 | r | map.soa.sf.R | map.soa.sf <-
function(xdata,ydata,date,rts,g,w=NULL,sg="ssm",mk="dmu"){
# Initial checks
if(is.na(match(rts,c("crs","vrs","irs","drs")))){stop('rts must be "crs", "vrs", "irs", or "drs".')}
if(is.na(match(sg,c("ssm","max","min")))){stop('sg must be "ssm", "max", or "min".')}
if(is.na(match(mk,c("dmu",... |
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