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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
39254583af1b1156f9bd21c96e5d8995233d860f | 50cae6d46e423d2fd3e5062bedf921adf232e8fb | /rscripts/enrichment_utils.r | 78d4c72d625eb3fbb48b9a72c4e65bf7bd236b09 | [] | no_license | bjcbjc/mylib | 779cd177cfbda7411f045f4aa045c7f37ff5c478 | 9c2d1bd3739b50bfe9e9c20a47971ade0ef67a5d | refs/heads/master | 2021-01-15T15:48:50.711618 | 2016-09-23T14:29:51 | 2016-09-23T14:29:51 | 12,460,362 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,088 | r | enrichment_utils.r |
enrich.go <- function (testGene, backgroundGene, inputGeneId= 'ENSEMBL', database= 'org.Hs.eg.db', ontologyList = c('BP', 'MF', 'CC'), extractGeneInGO = FALSE, pvalCutoff = 0.01, customMapping = FALSE, customMappingFile = '/nethome/bjchen/DATA/GenomicInfo/ENSEMBL/ensembl_entrez_10302014.txt') {
library(database, ... |
995aaff1e2a4c7391077047a898b43afc38a659a | 96ff9975086b3f791f02857b42a3ee29822946ea | /aer/chap01.R | 5b0fd795281bc1b9c2699275b72288f341953ead | [] | no_license | ecodiegoale/trading | 447f1175a42d3627067ff9bda391af837cfcbdb0 | b4e880799e8cb750a3aef95a51d463666a0870bf | refs/heads/master | 2021-12-05T23:21:15.281532 | 2015-08-24T16:10:18 | 2015-08-24T16:10:18 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,301 | r | chap01.R |
data("Journals", package = "AER")
dim(Journals)
names(Journals)
plot(log(subs) ~ log(price/citations), data = Journals)
j_lm <- lm(log(subs) ~ log(price/citations), data = Journals)
abline(j_lm)
summary(j_lm)
# experiment
plot(Journals$subs)
plot(log(Journals$subs))
plot(Journals$price / Journals$citations)
plo... |
4ea78bb143325bfd694bac669754bb5865e9847e | 880bb344072fa12bebaae9c0bc327b2a73a8adce | /man/transform_by_feature.Rd | 3ecf3dd3cc83701442b86aa7c79743895f86a011 | [] | no_license | zhuchcn/Metabase | a761b2efc3dc304bd35776d2fe2040e10a7ffa40 | 85306a15b540c307b073b65fdc860dfd3e0d91be | refs/heads/master | 2020-03-22T06:12:55.691167 | 2019-07-22T18:40:17 | 2019-07-22T18:40:17 | 139,618,397 | 1 | 2 | null | null | null | null | UTF-8 | R | false | true | 719 | rd | transform_by_feature.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Methods-mSet.R
\name{transform_by_feature}
\alias{transform_by_feature}
\title{Transform an mSet object by features}
\usage{
transform_by_feature(object, fun, ...)
}
\arguments{
\item{object}{An \code{\link{mSet-class}} or derived class objec... |
8f201f7b44af1a5749c94112121fe53a76c381b0 | 2487dfa8bb23d3e1a9000dba265c416cccb69939 | /demo/MCMCGuide11.R | 67f64f3f279ab2633f2f33c596c0f4f56b96bd07 | [] | no_license | cran/R2MLwiN | f2c5694b60e3a392ad516ab63689c642f3fc72bb | 593d94db244d3fc07538aedf83fc183859b9f5fd | refs/heads/master | 2023-03-21T15:14:11.554599 | 2023-03-14T04:40:02 | 2023-03-14T04:40:02 | 17,681,793 | 3 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,211 | r | MCMCGuide11.R | ############################################################################
# MLwiN MCMC Manual
#
# 11 Poisson Response Modelling . . . . . . . . . . . . . . . . . . . . 153
#
# Browne, W.J. (2009) MCMC Estimation in MLwiN, v2.13. Centre for
# Multilevel Modelling, University of Bristol.
##########... |
38b26f27dad13a7074d1ccb3d123edf6f981b187 | ae8016078b8562a186fc4b70d58e502299e948f4 | /R/dynrFuncAddress.R | 26739cf1cc43fbb3aa7ab2d41fd72a4e3bbfe9b5 | [] | no_license | mhunter1/dynr | 6c6a4a8527471306087a4e790cf5e98b3376c566 | 1f4f98d30ebc8a8ef8e90c1365b2d4b588922770 | refs/heads/master | 2023-07-21T11:05:48.652487 | 2023-06-30T14:24:09 | 2023-06-30T14:24:09 | 221,282,889 | 4 | 10 | null | 2023-07-02T18:00:14 | 2019-11-12T18:17:57 | R | UTF-8 | R | false | false | 9,560 | r | dynrFuncAddress.R | #--------------------------------------------------
# .C2funcaddresses
# Purpose:
# takes in a C file or C scripts
# returns a list of addresses of the compiled model functions and maybe R functions for debug purposes
#------------------------------------------------
# Changed DLL name and directory to be user-specif... |
c091b5cb7ffe4906f2e21dec1619d87f35a6495d | 5ef1116a839153add3d5e2d51751c81e169671b1 | /analysis/experiment_01/Analysis.r | 620c62126588342741512234dd9908c9c701dac8 | [] | no_license | adolfohermosillo/variable_telicity | 2f0889eeea52d46b5ff156982aa7529975da6ac8 | 207d19e404cf441e49354a542df2a145650c18bd | refs/heads/master | 2023-05-12T06:19:53.727947 | 2021-06-09T04:14:15 | 2021-06-09T04:14:15 | 353,233,905 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,806 | r | Analysis.r | library(ggplot2)
library(tidyverse)
library(lme4)
library(wesanderson)
library(languageR)
#importing data set
data <- read_csv(file = '/Users/jesushermosillo/Desktop/Spring 2021/LINGUIST_245B/variable_telicity/data/experiment_01/variable_telicity_and_verbs_of_consumption-merged.csv')
#labels for plots
data$levels <-... |
11b69eed558bc770a283f745503818cb87d971df | 7cecfa40ea47424e87af11659faa91e6c260fa8c | /man/longVarioMultiple.Rd | a6dc3df370dc75cf08c1779038fbb22d597f8aad | [] | no_license | PratheepaJ/bootLong | 7b444c006a98ef9370cc4247c312bb734420cd38 | 7986e753dd0e63e078631cec257f8550189183b7 | refs/heads/master | 2021-03-22T01:15:07.640516 | 2020-04-02T13:52:31 | 2020-04-02T13:52:31 | 121,357,751 | 8 | 2 | null | null | null | null | UTF-8 | R | false | true | 1,224 | rd | longVarioMultiple.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/longVarioMultiple.R
\name{longVarioMultiple}
\alias{longVarioMultiple}
\title{Plots the variogram for multiple taxa given the indices.}
\usage{
longVarioMultiple(pstr, main_factor, time_var, subjectID_var,
starttaxa = 1, endtaxa = 4, point ... |
f68963a78a112705dea421f9bfde18f4d9cb7c9b | b9121d329483b371fcd048e036661cfa288bfe08 | /lectures/data-raw/aklweather.R | 4d86e2860ca2a9a3c0e3592e4f96590e4a720b5f | [] | no_license | earowang/stats220 | 3ca02f5113294a40b3101edfe78e0edcda4c6ca2 | 183c260d3ac3036f4e842829f8f6501c1da3c33e | refs/heads/master | 2023-08-26T02:48:58.138357 | 2021-06-07T22:55:18 | 2021-06-07T22:55:18 | 242,031,925 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 995 | r | aklweather.R | ## code to prepare `aklweather` dataset goes here
library(tidyverse)
library(lubridate)
# Read stations data
stations <- read_table("data/ghcnd/ghcnd-stations.txt",
col_names = c("id", "lat", "lon"))
library(ggmap)
akl_box <- c(left = 174.69, bottom = -37.09, right = 174.94, top = -36.60)
akl_map <- get_map(akl_box)... |
86534c8472247e824f086203302cc619e8499e6e | c7ea7d89e36aa3d38924f2ee32f286e3a88b7ee6 | /ui.R | 5be88678617f353b26e01fcd07f84812cf564e7b | [
"MIT"
] | permissive | guptatan/staff_projection | 2503f3b1b4d4eab73a7b12312c8a5a8c8a30d3ae | be9c03eb43e508b8b4bd07b734b39d49cc8541ec | refs/heads/master | 2023-07-14T19:22:54.894761 | 2021-09-01T17:39:59 | 2021-09-01T17:39:59 | 254,688,075 | 0 | 0 | null | 2020-04-10T16:53:53 | 2020-04-10T16:53:52 | null | UTF-8 | R | false | false | 9,060 | r | ui.R | library(shiny)
library(tidyverse)
library(rhandsontable)
library(highcharter)
library(shinyjs)
library(plotly)
# Define UI for application that draws a histogram
shinyUI(
fluidPage(
includeCSS("styles.css"),
titlePanel("Project Your Staffing Needs"),
# Start - Sidebar
sidebarLayout(
sidebarPane... |
e6e398f958aad4af4394bc225d29ce4599aad217 | a176626eb55b6525d5a41e2079537f2ef51d4dc7 | /Uni/Projects/code/P046.Israel_MAIAC/archive/cnnew/buildfiles/aq25_body.r | ac946605adc102e054123447f1e4f5be6fad0434 | [] | no_license | zeltak/org | 82d696b30c7013e95262ad55f839998d0280b72b | d279a80198a1dbf7758c9dd56339e8a5b5555ff2 | refs/heads/master | 2021-01-21T04:27:34.752197 | 2016-04-16T04:27:57 | 2016-04-16T04:27:57 | 18,008,592 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 22,563 | r | aq25_body.r | #-------------------> Year 2010
#if needed load res table
#res<- readRDS("/media/NAS/Uni/Projects/P046_Israel_MAIAC/3.Work/2.Gather_data/FN000_RWORKDIR/resALL.AQ.rds")
### import data
m1.2010 <-readRDS("/media/NAS/Uni/Projects/P046_Israel_MAIAC/3.Work/2.Gather_data/FN000_RWORKDIR/mod1.AQ.2010.rds")
################# ... |
7c965adfddf66cb80cc52fd4f5ad5d830443692b | 92b79862c8bcb6b8056ea2cfc2609e07c29c5377 | /PCAExample.R | 42b9d5b89bdf0fb8bb99d2047317685e9ad77b72 | [] | no_license | d0p34m1n3/PortfolioOptimisation | 8cd647cdad6966fa26ae7136b8515334ba870dd6 | a6d5c24efd9032f5075b9e90a906f6e3491d1542 | refs/heads/master | 2020-04-13T17:08:19.121951 | 2015-05-15T12:28:13 | 2015-05-15T12:28:13 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 960 | r | PCAExample.R | rm(list=ls())
require(RCurl)
sit = getURLContent('https://github.com/systematicinvestor/SIT/raw/master/sit.gz', binary=TRUE, followlocation = TRUE, ssl.verifypeer = FALSE)
con = gzcon(rawConnection(sit, 'rb'))
source(con)
close(con)
load.packages('quantmod')
data <- new.env()
tickers<-spl("VBMFX,VTSMX,VGTSX,VGSIX")
... |
5d2130606abcd213a0b066cabd6189d05a0fd1f6 | b3b3e49423863dee73cc9d02d69e1bc029f51dd2 | /man/methodList.Rd | 87b54cc23ce3e1588646f6556df5564d2687b2d6 | [] | no_license | vjcitn/benchOOM | 0fc5d6d8160f84bf3f89eb87c773212007af9dc8 | e6983335cdfb974e53568c8954eed5ff3d643ed9 | refs/heads/master | 2021-07-09T10:20:01.712116 | 2021-04-16T03:59:01 | 2021-04-16T03:59:01 | 80,768,960 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 375 | rd | methodList.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dataBench.R
\name{methodList}
\alias{methodList}
\title{helper for creating a methodlist}
\usage{
methodList(methods = c("hdf5", "bigm", "sqlite", "ff"))
}
\arguments{
\item{methods}{a character vector with tags for available round trip metho... |
208aff327cebf909cbf866d65d053f2754701711 | 86976cc7492495a5a5bcb2f5ffa63731a634768c | /man/ShakespeareWordHist.Rd | d06c9545acc78c82e91b8894624e06c9de384fa0 | [] | no_license | GiancoAngelozzi/preseqR | e9d9d84bd1c4d5584d0d98ea380ca85f98787a4e | 99362f67dd09b15722cb91632f5be1784251751d | refs/heads/master | 2021-01-12T19:59:38.680781 | 2015-06-04T00:00:00 | 2015-06-04T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 474 | rd | ShakespeareWordHist.Rd | \name{ShakespeareWordHist}
\alias{ShakespeareWordHist}
\docType{data}
\title{Shakespeare's word type frequencies}
\description{The Shakespeare's word type frequencies data was from
Efron, B., & Thisted, R. (1976).}
\references{
Efron, B., & Thisted, R. (1976). Estimating the number of unseen species:
How many words di... |
66a1389ee50ff5ca0dc8f7e18a6be8cd65b8a8ba | e9da61695d915c1ea1cd76dbf644b149b4c8c690 | /Code/R/setup.R | f64da57c34331debebb118b5443e4a658a4405b6 | [] | no_license | gbohner/Cambridge_talk_20190306 | 90aa3a485dfeb7328d7fb9d5c36e5c5091b28569 | 90c43c7e889fc47bab3b74d465a9ae54c3f5a56b | refs/heads/master | 2020-04-25T04:40:39.922001 | 2019-03-05T20:50:01 | 2019-03-05T20:50:01 | 172,518,640 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 612 | r | setup.R | setwd("~")
system("cd ~")
if (!file.exists("Cambridge_talk_20190306")){
system("git clone https://github.com/gbohner/Cambridge_talk_20190306")
}
setwd("~/Cambridge_talk_20190306")
system("git pull")
setwd("~")
system("cp ~/Cambridge_talk_20190306/Code/R/* ~/")
# Set the libPaths to the already installed packages
cur... |
800b08459f4d77ddc763e52784a71ec3d2a88250 | 43332ed929f6417071c96464de00d1c5caf5df98 | /R/geom-segment2.R | e8d8c2e9b4abb65dd01e1c02e1cbde4a0c7a5a89 | [] | no_license | aaa7260/ggcor | e81a305855b724abaa4e115b29e40d582b2ac1a3 | dd3687430b77a9326dfcc258d359ac7c108a65ad | refs/heads/master | 2023-02-27T00:15:07.307000 | 2020-07-22T13:44:24 | 2020-07-22T13:44:24 | 334,437,269 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,742 | r | geom-segment2.R | #' Segment2 layer
#'
#' @inheritParams ggplot2::layer
#' @inheritParams ggplot2::geom_segment
#' @section Aesthetics:
#' \code{geom_segment2()} understands the following aesthetics (required aesthetics are in bold):
#' \itemize{
#' \item \strong{\code{x}}
#' \item \strong{\code{y}}
#' \item \stron... |
b88130c7f952c7bf0b2141c7556c7023edb8d651 | 3db221fa13b0806047df98103c0c03df5520cc9b | /R scripts for analysis/export_data.r | 08b2856815f7c254b8594ca0da72c89b131de0e2 | [] | no_license | xsatishx/cloud-repo | 55d48aa37ecb7daf772d754e3c2e74a7f6819349 | 50bc0d4ecda5a09bdf29cf78ffdd8c72d59d8f7f | refs/heads/master | 2020-12-25T16:54:21.281357 | 2018-10-24T04:38:46 | 2018-10-24T04:38:46 | 49,554,166 | 1 | 2 | null | 2020-07-24T04:39:07 | 2016-01-13T06:23:16 | HTML | UTF-8 | R | false | false | 163 | r | export_data.r | export_data <- function(data_object, file_name){
write.table(data_object, file=file_name, sep="\t", col.names = NA, row.names = TRUE, quote = FALSE, eol="\n")
}
|
d917e63728782522208321f25a76d192e9c581be | 92e240738a4ccf673b9f3610386eaa08eef26d6f | /volatility/momentum/study.R | 6b0b368177dd139818bc662ad5f31685748af051 | [] | 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 | 4,702 | r | study.R | source("d:/stockviz/r/config.r")
source("D:/StockViz/public/blog/common/plot.common.R")
reportPath<-"."
library('RODBC')
library('quantmod')
library('PerformanceAnalytics')
library('lubridate')
library('tidyverse')
library('reshape2')
library('ggthemes')
options(stringsAsFactors = FALSE)
options("scipen"=100)
pdf(N... |
5596e5d141205e3ef858bb4fe388a5f6d9e1eb36 | fb31e635792ce4ffbcaff2e145a6fbb37d7e9852 | /man/truncation.Rd | 8f787d4a44957df2196b398304c0828da4df6bf1 | [] | no_license | khliland/plsVarSel | 57c3ccfefcbe549b0fcdff452e581e1b0db0833f | 5c08b5b59444de3505fe579b12cbc46ddad4f3dc | refs/heads/master | 2023-01-24T07:50:38.251503 | 2023-01-12T10:35:48 | 2023-01-12T10:35:48 | 55,041,088 | 1 | 3 | null | null | null | null | UTF-8 | R | false | true | 2,319 | rd | truncation.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/trunc.R
\name{truncation}
\alias{truncation}
\title{Trunction PLS}
\usage{
truncation(..., Y.add, weights, method = "truncation")
}
\arguments{
\item{...}{arguments passed on to \code{mvrV}).}
\item{Y.add}{optional additional response vector... |
8def0853f7552a2a1fafa543053997c14d718922 | 5a7523ffc00dfaee9d283f12d8e6f6e761ad4afa | /logreg code.R | 8c1260b367c87ae7438eb4f8e8eaee7d7d1cc80e | [] | no_license | ellierk/honors-thesis | 8a6854cde600639ef9c46450cb5a9c4c2c71e3a8 | 0ac22674e98a80cb14dc88d2883d04121d7bfbd1 | refs/heads/master | 2023-01-11T09:18:38.728534 | 2020-11-19T02:19:57 | 2020-11-19T02:19:57 | 296,682,069 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 991 | r | logreg code.R | df1 <- squid %>% select(site, date, spacing_m, temp_avg, sal_avg, dist_from_bags, reclaimed, absent)
df2 <- df1[1,] %>% mutate(consumed = "1")
v = df1$reclaimed
i = 1
l=1
while(i < length(v)) {
l=1
while(l < v[i]) {
ifelse(l < df1$absent[i],
(df2 = df2 %>% add_row(site = df1$site[i], date = df1$dat... |
354b67fd613f866810f70f3a525224aaca65f45a | e9af29f8578f6fed182a12d625b6e846b3c3086b | /cds/exdata/week3/03_04_R_colors.R | 4cda29650f48cc18fc6ea541352dd6a99d013af7 | [] | no_license | ceik/coursera | 05750f640d98ffdfb4853871e3ae0c9c1ef86851 | 751a04177990edd7ba7c5a8c6bd976dcfcb62dfc | refs/heads/master | 2021-01-10T13:28:38.220484 | 2018-10-28T08:10:59 | 2018-10-28T08:10:59 | 50,228,306 | 0 | 0 | null | 2016-01-24T12:47:38 | 2016-01-23T07:22:44 | HTML | UTF-8 | R | false | false | 3,429 | r | 03_04_R_colors.R | ##### Plotting and Color in R #####
#########################################
### Problem
# Colors can make it much easier for the reader to understand your data/plot.
# The default color schemes in R are often suboptimal. This is true both from a
# design and a functional (colors are often supposed to illustr... |
bb621f18b6639bd9266b4edd7506d4b14f73d235 | c18fdf99a4972d7c8da846723283578ec6a6584e | /montecarlo/test.R | d59a2adbc9fc080fcf34ce08f27bfdd616a5ae40 | [] | no_license | jiqis/sandbox | 39ce6c11a7059652af4fa0c71bc0f2c88569aa49 | a38470689c818d3a526f7458ce731692a295cc9a | refs/heads/master | 2021-09-21T16:42:04.086678 | 2018-08-29T00:37:55 | 2018-08-29T00:37:55 | null | 0 | 0 | null | null | null | null | MacCentralEurope | R | false | false | 153 | r | test.R | #ÉtÉ@ÉCÉč
data <- read.csv("./data.csv")
data.temp<-data$average_temperature
data.dlen<-data$day_length
m1<-lm(data.temp~data.dlen)
summary(m1) |
60517d296f758ec86438883f4fc5a6c47e47753d | e6d29f8a2fea50e45e37285d3d47985763fd8c03 | /man/ipaq_scores.Rd | b419e4e9fb1ee0e8e57a25d10f2741f0cdca121a | [
"MIT"
] | permissive | Mariana-plr/IPAQlong | de0b7b8d532e2d3dccd20204c42911b8c0f897c2 | 6f57ae46fa8779e08fa8efac56ce9b394b8f267e | refs/heads/main | 2023-08-04T09:11:44.930621 | 2023-07-29T12:03:08 | 2023-07-29T12:03:08 | 471,093,506 | 1 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,143 | rd | ipaq_scores.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ipaq_scores.R
\name{ipaq_scores}
\alias{ipaq_scores}
\title{IPAQ scores}
\usage{
ipaq_scores(data, truncate = F)
}
\arguments{
\item{data}{A data frame object containing 25 columns with the replies to the IPAQ long format (parts 1-4).
Yes/no ... |
82f3d969d6eba6c1e92a8d496424703d44aa8567 | e4ff3a5fc17302d8d4fd86b38072e67ffe1aedec | /man/wfshat.Rd | 00f3e770e45a8b753bfeca6750bd85eefca32d22 | [] | no_license | cran/robeth | 5782cfcb86e6931152dc8a0b9b8f71e97068e449 | 5b60aabc7c1b21f15d73d1246ab40c1defdf5f7f | refs/heads/master | 2023-08-31T11:44:10.694653 | 2023-08-22T08:00:05 | 2023-08-22T09:31:11 | 17,699,284 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 482 | rd | wfshat.Rd | \name{wfshat}
\alias{wfshat}
\title{ Schweppe original weight proposal }
\description{
See Marazzi A. (1993), p.137}
\usage{
wfshat(xt, n = nrow(xt), sh)
}
\arguments{
\item{xt}{ See reference}
\item{n}{ See reference}
\item{sh}{ See reference}
}
\value{
See reference
}
\references{
Marazzi ... |
e0cfd4eb6ce27bd1346a03d8212383c8dc992a2a | 8a6e3522bfbefa3abd245ff413bc5824544bc231 | /R/print.summary.spsur.R | 2a2bab75a27651aa961c83ce65139bc6a9f0900e | [] | no_license | rominsal/spsur | be3f1a338b9ba97750ed3c8dfd0ab1aea0b4170c | 75fc1a8d6fbf91572f65d64df030d20c0aea6dc0 | refs/heads/master | 2022-05-14T12:36:34.534139 | 2022-04-22T20:43:55 | 2022-04-22T20:43:55 | 131,492,488 | 12 | 4 | null | 2022-04-22T20:43:55 | 2018-04-29T12:25:20 | R | UTF-8 | R | false | false | 2,605 | r | print.summary.spsur.R | #' @name print.summary.spsur
#' @rdname print.summary.spsur
#'
#' @title Print method for objects of class summary.spsur.
#'
#' @param x object of class \emph{summary.spsur}.
#' @param digits number of digits to show in printed tables.
#' Default: max(3L, getOption("digits") - 3L).
#' @param ... further arguments pas... |
ed5f6d1fccfd130dbd971cfe390dec078f7e9b91 | 4d286db1d87c5adcaaf3e19b3022090f316aa794 | /scripts/Group_google.R | 3354a5d7a3dc673c65be16164f5c9b10cecd1d6e | [] | no_license | MortonArb-ForestEcology/Phenology_Forecasting | 06dbad302ac334b6f335cbe5796479b51cad09f8 | f1f19696dc938ab0edb2a80c398ad3b28dd8e898 | refs/heads/master | 2023-04-30T02:50:57.704185 | 2023-04-18T17:35:40 | 2023-04-18T17:35:40 | 249,529,541 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,247 | r | Group_google.R | #----------------------------------------------------------------------------------------------------------------------------------#
# Function by : Lucien Fitzpatrick
# Project: Living Collections Phenology Forecasting
# Purpose: A function that will download all of the google forms of interest
# Inputs: 2018 to prese... |
367ddbe70595a3267ba6d5752d952f29d2b91117 | a24962c483b7e4366b7dba2bad71423962cdd6e4 | /examples/examples.exp2.R | b0558337e89edf4de0dc38b4805b3b8f5257e0a0 | [] | no_license | singmann/acss | ebbbaddbd1ee9b234d7c681464328ef28e200f0d | cc694cb7ed01b3e43f43b6dae832947aff84ccca | refs/heads/master | 2020-04-06T14:59:17.739935 | 2016-09-01T07:25:38 | 2016-09-01T07:25:38 | 14,473,891 | 4 | 1 | null | 2013-12-14T20:57:35 | 2013-11-17T20:13:39 | R | UTF-8 | R | false | false | 569 | r | examples.exp2.R |
# load data
data(exp2)
exp2$K <- acss(exp2$string, 6)[,"K.6"]
m_log <- glm(response ~ K, exp2, family = binomial)
summary(m_log)
# odds ratio of K:
exp(coef(m_log)[2])
# calculate threshold of 0.5
(threshold <- -coef(m_log)[1]/coef(m_log)[2])
require(effects)
require(lattice)
plot(Effect("K", m_l... |
2ff78d5ee461ff70a782942a55f56e494e12f27f | 44598c891266cd295188326f2bb8d7755481e66b | /DbtTools/GraphAlgorithms/man/PlotGabriel4BestMatches.Rd | 28bab1a5e783eae83b66496da7a72d4a98dc82ac | [] | no_license | markus-flicke/KD_Projekt_1 | 09a66f5e2ef06447d4b0408f54487b146d21f1e9 | 1958c81a92711fb9cd4ccb0ea16ffc6b02a50fe4 | refs/heads/master | 2020-03-13T23:12:31.501130 | 2018-05-21T22:25:37 | 2018-05-21T22:25:37 | 131,330,787 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 902 | rd | PlotGabriel4BestMatches.Rd | \name{PlotGabriel4BestMatches}
\alias{PlotGabriel4BestMatches}
\title{Plot Gabriel4BestMatches}
\description{
Zeichnen des Delaunay Graphen, Punkte ggf. nach Cls gefaerbt
}
\usage{
PlotGabriel4BestMatches(BestMatches,MatrixOrSize,Cls,IsTiled)
}
\arguments{
\item{BestMatches}{BestMatches, (1:d,1:3)}
\it... |
93c571391fd3f5b2b105d4a1bb2330a0eb35c343 | 76b1a90fa416132972b40e40323a156060ada7ba | /man/print.ckmr.Rd | b6ee1119c8b4fdab86d7fba1d730147afc1c7a35 | [] | no_license | krshedd/CKMRsim | 8b558df4bd241e9990fecefac072d46b771bec93 | 930d7fc6523071fe9de857224e400a8281c43b81 | refs/heads/master | 2020-04-07T07:04:49.295560 | 2018-11-19T05:26:06 | 2018-11-19T05:26:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 329 | rd | print.ckmr.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ckmr-class.R
\name{print.ckmr}
\alias{print.ckmr}
\title{print method for ckmr class}
\usage{
\method{print}{ckmr}(C)
}
\arguments{
\item{C}{an object of class \code{\link{ckmr_class}}.}
}
\description{
Just wraps a call to the format.ckmr fu... |
1a953da741d2571bc8b60b6122988f0bf9cd7285 | 07c8bb22b912f441b9fcaa46b4080ec141a0943e | /day2examples.R | 5944606b6f840ab553d0be43e3abbaa7b4e34d13 | [] | no_license | thepingryschool/r-examples-at | 382e21be5775179a845f3eb0166bb7a797c7164a | bad6ad8f50e2fd447a57df1bd5beda47802aa622 | refs/heads/master | 2020-04-01T23:33:46.691952 | 2019-01-10T18:28:34 | 2019-01-10T18:28:34 | 153,763,777 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 756 | r | day2examples.R | # This example script shows the properties of vectors
# 2 ways to create a vector
v1 = c(1L, 2L, 3)
v1
v2 = seq(1, 10)
v2
v3 = 1:10
v3
# coercion
v4 = c(1L, 2L, 3, "4", "h")
v4
print("-------------------")
#vectors hold same type
typeof(v1)
class(v1)
typeof(v2)
class(v2)
typeof(v4)
print("-------------------")
#l... |
0c4099eab2e20ee75616304cef6ed8d3163de716 | 4903d9852fc3f599ee04d03312ef69ee40adfc27 | /plot2.R | 75544071e73db3d936fa3cb5f4e1e4ff8017dc71 | [] | no_license | sarahkurihara/ExData_Plotting1 | aae4f42cd8fc88612429f582997ebdac6a89e91b | 37a8b1f55e812bd139f6bcbc725ea9ff83c31f4e | refs/heads/master | 2022-06-23T17:23:21.958110 | 2020-05-09T21:44:56 | 2020-05-09T21:44:56 | 262,641,819 | 0 | 0 | null | 2020-05-09T19:15:47 | 2020-05-09T19:15:46 | null | UTF-8 | R | false | false | 504 | r | plot2.R | plot2fn <- function() {
##load data
data <- read.csv("household_power_consumption.txt", header = TRUE, sep = ";")
##subset data from the dates 2007-02-01 and 2007-02-02
data <- subset(data, Date == "2/2/2007" | Date == "1/2/2007")
#Convert date and time
datetime <- as.POSIXct(paste(data$... |
98f932d411577c4e9fd668f1de9b17d57d986906 | 4e344e89e17232cb54a233a642bcc27cf64e9efc | /R/loadDefinitiveModel.R | a4e5f935d89ce6fe972103935b9531d70bfdf46a | [] | no_license | jamiepg3/mopa | f02d79fd51a5a83b6b1f8c497e6aaaf81686ecab | 23ab02fe342ae4421a65c07bec2ee4f3ba2efea8 | refs/heads/master | 2017-11-30T17:22:59.545467 | 2015-06-10T07:31:05 | 2015-06-10T07:31:05 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,996 | r | loadDefinitiveModel.R |
#' @title Load Rdata files storing definitive fitted model
#' @description Load information from Rdata generated with function allModelling based
#' in an index to select the definitive fitted model/s, ideally, the index returned by
#' function indextent should be used.
#'
#' @param data Object with the same str... |
45d61c65c2dc5647e0fb567508176e0abbc8efda | 3cf7dbc603a37c4b1609913acb5f693e8bc6f2c5 | /diamonds.R | 1e18140446ca29d00c53207e01d7d92d24645e66 | [] | no_license | ckp-koiken/R4DS | 6c579f3e5649675c8b70161f07859b042b173d0e | b491461b88a4f2208fb2a3e18e1622ec8f2a0e4d | refs/heads/main | 2023-04-12T09:10:43.145617 | 2021-05-13T04:23:37 | 2021-05-13T04:23:37 | 366,662,265 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 236 | r | diamonds.R | library(tidyverse)
# 6章 ワークフロー：プロジェクト --------------------------------------------------------
ggplot(diamonds, aes(carat, price))+
geom_hex()
ggsave("diamonds.pdf")
write_csv(diamonds, "diamonds.csv")
|
507ab5ea5e9e897b6f7f23872f2d9003e41a1895 | 96e6210bf4b9c0573621772bf42790e7b675c37c | /Data Analysis/YaoZhang_HW2.R | d692c2d53e97fb50980cd8654dca2d477a5e71fb | [] | no_license | ohana1128/HW | ede2dd666df37c2a22b4523c21f95c6b23586c2a | 2aadc47bb54be650cf34536b88add39ced1caacd | refs/heads/master | 2021-01-19T04:15:37.060084 | 2016-09-13T20:19:35 | 2016-09-13T20:19:35 | 45,416,689 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,124 | r | YaoZhang_HW2.R | pain <- read.csv("HW2Data2.csv")
dim(pain)
##1.Draw a boxplot for pain relief scores against different pain levels.
library(ggplot2)
ggplot(pain,aes(x=factor(PainLevel),y=Relief))+geom_boxplot()
##2.Perform a single factor ANOVA and compare the differences in “Relief Scores” of each “PainLevel” group.
##check normali... |
7962ee999a31cbfa891b8ca60f99668d27d92ccb | 16f8c4d8fdda15632647077bdee8cf4289219202 | /R/b_ssa_analysis_1dssa.R | 4189b5d3b4b2a806ce8f0375bd67a20c297394f0 | [] | no_license | polinazhornikova/Thesis-2018 | 34ec066684ea54f591b8c1b33e634420798334ba | 70f2597bbab8d8f5bdc2b9b0a4cf3b4c58495013 | refs/heads/master | 2020-03-17T17:25:54.787365 | 2018-06-05T23:25:00 | 2018-06-05T23:25:00 | 133,788,036 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,090 | r | b_ssa_analysis_1dssa.R | ###Fragment initial
fragmentStart("fragments_ch1/1dssa_init.tex")
source('main.grouping.auto.R')
library(lattice)
library(Rssa)
N <- 199
omega1 <- 0.1
omega2 <- 0.25
fragmentStop()
###end
###Fragment 1dssa_series
fragmentStart("fragments_ch1/1dssa_series.tex")
x <- exp(0.01 * (1:N)) + 2*cos(2 * pi * omega1 * (1:N)) +... |
2860cdfbfc589f6efcdf6de04c7d3f9736b0e319 | f6275d025b109bac1c648e5f3e3df5525f4a6966 | /WikiMultipleMonths.R | b543941040b6e58be57ac50c4f370c7ae57d34f3 | [] | no_license | bladster/RStudio | f8e2e221be850141a271393dc3b7a9ab6ed6537f | 41f50dc200e81c30ee8ff8617c856e04734b84ca | refs/heads/master | 2021-01-01T04:26:55.438647 | 2016-05-04T13:35:51 | 2016-05-04T13:35:51 | 58,054,704 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 430 | r | WikiMultipleMonths.R | allURLs <- NULL
for (year in (2008:2014)) {
for (month in (1:12)) {
if ((year == 2014) && (month > 10)) {
next
}
theURL <- "http://stats.grok.se/json/en/"
theURL <- paste0(theURL,year)
if (month < 10) {
theURL <- paste0(theURL,"0")
}
theURL <- p... |
298acda74a98daa6e9bd8bbeb3892c447eef8cab | 0b01338c904a2662bc925a5df0462ae36f2210c4 | /14_QCmetrics.R | f337fa9ca357f8d311ce649d4b58e429dbed5f6d | [] | no_license | JMF47/recountNNLSpaper | 946980021d82e1b73eafab1fb69534e2c8d962fa | d251efaae1a20f2d96bf2f103445ab8a68905fc2 | refs/heads/master | 2021-09-14T12:20:29.791693 | 2018-05-13T17:22:10 | 2018-05-13T17:22:10 | 117,008,135 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,657 | r | 14_QCmetrics.R | ### Spot-check
rm(list=ls())
library(GenomicRanges); library(rtracklayer); library(stringr); library(Biostrings); library(Rsamtools)
library(SummarizedExperiment); library(recountNNLSdata); library(recountNNLS)
url_table <- recount::recount_url
unique_ids = unique(url_table$project)
unique_ids = as.character(unique_i... |
c605faef4cf85a5b16136c40fc8fd801f2447c02 | 22b36960caa879eb916d08e47b13b0ad0cc3ac2d | /config.R | 5118b7436d296c163a58a0829ae127530545c453 | [] | no_license | labepi/tsclas | 09f845def04444f987c52d2c5eb357143565da23 | fb26127bb90995a98b597f6918bf3a3fbd067a74 | refs/heads/master | 2023-04-25T00:51:05.772334 | 2021-05-15T23:30:07 | 2021-05-15T23:30:07 | 276,223,623 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 630 | r | config.R | # path to the bandt-pompe functions
bandt_pompe_path="../bandt_pompe"
# path to the skinny-dip files
skinnydip_path='../skinny-dip/code/skinny-dip'
# path to datasets
dataset_path='./data'
# print the debug messages
DEBUG=TRUE
# to load the pre-computed features for a given dataset
LOAD_PRECOMPUTED=TRUE
#LOAD_PRECO... |
c45e7d0abc49e404d5f2f56274ae886c99a13091 | d1a388b98b8c248c5f0388672189acedf96b0a93 | /Simulation_juin2018/Estimation Paper 2 juin 2016/Calibration HN/Calibration Price Linear/Methode HN.R | e67ae1b03581effdef29117636d1e4063597f86f | [] | no_license | Fanirisoa/dynamic_pricing | 1951438ea282358cf0aa90a04b1273846cd70836 | 66722ae75f446a3c9e2a672890ae808c679f72cd | refs/heads/master | 2023-04-09T04:36:15.646529 | 2021-04-20T19:38:35 | 2021-04-20T19:38:35 | 212,493,315 | 3 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,075 | r | Methode HN.R | rm(list=ls())
gc()
library(compiler)
enableJIT(1)
enableJIT(3)
#####################################################
### Load both data.contract and data.ret #######
#####################################################
load("DataPrice2009.Rdata")
## load("Dataprice2010.Rdata")
####################... |
32daba3c3a24fc13aa539713447441d5e72451d7 | efcdc10a70c28a624b812d20cb5777f848b59a54 | /simulate_Exp.R | 168c1fde7c9de0c7b84165482d04d8ff1655b081 | [] | no_license | glmbraun/mNodes | fdb6437ec34330b6be0f2a330b23ebbee5c612ef | 05d136498a55902b55a3457bb467963ac679a8b2 | refs/heads/master | 2022-12-24T02:25:31.456026 | 2020-09-16T09:56:54 | 2020-09-16T09:56:54 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,089 | r | simulate_Exp.R | # Load packages
library(Matrix)
library(lbfgs)
library(ggplot2)
library(dplyr)
library(RSpectra)
library(aricode)
library(kpodclustr)
library(janitor)
library(tidyr)
library(purrr)
library(grid)
library(microbenchmark)
library(foreach)
library(doParallel)
library(igraph)
library(gridExtra)
library(lemon)
library(latex2... |
2e470ed0828738f6564344f695eb503550bbd434 | 0f7405b90fade51b2ce5218869513065f8c6ad34 | /R/GammaExample.R | de9389f1a71ba10f9300533bf8f82412f782ed99 | [] | no_license | anhnguyendepocen/AdvancedRegression | 4dcaf01554af22c27b51f39094149f6bbdada810 | 5bbd35c8196759dd80bea953a13faa80c8764b99 | refs/heads/master | 2022-03-09T23:29:17.615787 | 2019-10-05T14:08:37 | 2019-10-05T14:08:37 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,383 | r | GammaExample.R | #' GammaExample
#'
#' Using the \code{real estate} data, perform a regression using
#' a box-cox transformation
#'
#' @return Nothing
#' @export
#' @importFrom tibble tibble
#' @importFrom magrittr %>%
#' @import stats
#'
#' @examples{
#' GammaExample()
#' }
GammaExample <- function() {
real.estate.data <- AdvancedR... |
aa1848502b82f92e5c16e26b730ba6426d6f2160 | ed558382701960dd53b98c2a6501ce40170015d1 | /qtls_input_data.R | d94579be1f70c1ea00b961f5b609f5a52b446e2d | [] | no_license | Diennguyen8290/gtex_deconvolution | 93fd08039b71baed4de0ba12563f5701593d8bb7 | fc8f11eb988c51cddc3472f94990f2cfa7fae1d6 | refs/heads/master | 2022-02-19T11:00:42.997817 | 2019-09-17T20:18:27 | 2019-09-17T20:18:27 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,249 | r | qtls_input_data.R | message("Loading input data...")
bcftools = "/frazer01/software/bcftools-1.9/bcftools"
vcftools = "/frazer01/software/vcftools-0.1.14/bin/vcftools"
rscript = "/frazer01/home/matteo/software/R-3.5.1/bin/Rscript"
ipscore_vcf_input = "/frazer01/projects/reference_files/cellType_Invariant/IPSCORE_WGS.biallelic.b37.vcf.g... |
b23cfe608ae0c72470fda9ed6c9e113246ba1811 | 55f40ba14ebc4cfe0e01023ec96cbf0550576e06 | /bayeosSpreadsheet/R/spreadsheet.R | 9fd8182ef230f3b44a72e0a1f25f348fc1f7c5ea | [] | no_license | BayCEER/BayEOS-R | ee3d1039aca045454bf1d8c51944595a8b76aaa6 | c7d4e5f93e0949c6d19a5a7e5ba35a69aab51adb | refs/heads/master | 2022-12-10T12:05:08.935235 | 2022-12-08T12:53:44 | 2022-12-08T12:53:44 | 68,090,578 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 5,217 | r | spreadsheet.R | # Came from RExcelML
if(FALSE) {
setClass("OOWorkbook", contains = "ZipArchiveEntry")
setClass("OOWorksheet", representation(content = "XMLInternalDocument", name = "ZipArchiveEntry"))
setClass("OOWorksheetFile", contains = "ZipArchiveEntry")
setMethod("names", "OOWorkbook",
function(x) {
doc... |
42bfab76a271129480e020b90c0b537765877a6c | 60a0c792683c89108386e03a67e3b84560d61a10 | /R/install_pip.R | 8473b64797b46338f88aaa9c42aa239421c7bccc | [] | no_license | cran/mhcnuggetsr | ec51828c2ec775d837a705cff14dc2fe77e62c90 | e781842724b9c950524f6e17c47717325cfca6c2 | refs/heads/master | 2023-01-20T20:23:10.719279 | 2020-11-04T10:30:02 | 2020-11-04T10:30:02 | 310,515,922 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 432 | r | install_pip.R | #' Install pip.
#' @return Nothing
#' @examples
#' \dontrun{
#' install_pip()
#' }
#' @author Richèl J.C. Bilderbeek
#' @export
install_pip <- function() {
script_filename <- tempfile()
utils::download.file(
url = "https://bootstrap.pypa.io/get-pip.py",
destfile = script_filename,
quiet = TRUE
)
... |
5cbaa298693e57d482904f3fc42ab0e295e5d404 | 9f0cd62433a8c400113076c35454683a84b9fc64 | /R/synth_diff.R | 9186cf495515763b2386b0f31bcbae25eb18e9b4 | [
"MIT"
] | permissive | MatthieuStigler/multiDiff | 6c88f683290b9802dc952df79747df1a39f49fa5 | 6c9aff0a7d77089f1b740762d2037e411e248a23 | refs/heads/master | 2023-09-03T00:54:24.226258 | 2023-08-23T12:57:52 | 2023-08-23T12:57:52 | 190,827,577 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,751 | r | synth_diff.R | #' Run synthetic diff-diff
#'
#' @template param_mdd_dat
#' @param add_weights return the weights?
#'
#' @examples
#' if(require(synthdid)){
#' data('california_prop99')
#' mdd_california_prop99 <- mdd_data_format(california_prop99,
#' y_var = "PacksPerCapita",time.index =... |
b9f5c5e47eb03c4bbac6c8bdf32360fbf75ac185 | b74674a867526ef01ad189adda2da14b8be4fa59 | /R/account_account_timezone.R | ec949b1b8a20ac64b835b9dc930e910a2ddd50b3 | [
"MIT"
] | permissive | brandseye/brandseyer2 | d33a84c7194b397068793da6a305154addf73aa2 | 59fab98f11b9b05cbe5cac6409b2453374b7267e | refs/heads/master | 2021-09-15T17:17:38.686089 | 2021-09-01T19:04:48 | 2021-09-01T19:04:48 | 132,138,395 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,932 | r | account_account_timezone.R | # Copyright (c) 2018, Brandseye PTY (LTD)
#
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish... |
602b11e3dba58f66c26e647b00e204363318d9f1 | eb2cd7490e2e4fc1c18fed6019c3888892b6bb0d | /Assignment_3/p7/GaussianProbability.R | 9031cf352bc33d9604aa0d13127b649e0ae34737 | [] | no_license | ksingla025/Machine-Learning-Assignments | 8f75e1a36de1cfdffcba7fe2826c559cb0171bb6 | 0ea8518af52b080ac6635782f1952437e2d3674d | refs/heads/master | 2020-05-18T08:29:39.321179 | 2014-11-22T12:38:04 | 2014-11-22T12:38:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 99 | r | GaussianProbability.R | GaussianProbability <- function(x, mean, sd) {
(1/(2*pi)) * exp(-1 * ((x - mean)^2)/(2 * sd^2))
} |
d26ce92a822121844f4b333ac928b9dc7105c9fa | e79df1c2164b29c127c2102bc4495b2384f3895e | /R/attribute_scrap.R | d10e1af5fa0d698f27373207e32614bcdb2d6638 | [
"CC-BY-4.0",
"MIT"
] | permissive | feddelegrand7/ralger | 1b263a3c15c3b208a96a633f30ec2433efb4aabc | 57ebc6b07511675c23d91007e701a9722aeb86d4 | refs/heads/master | 2023-03-13T08:54:24.066033 | 2023-03-05T20:41:03 | 2023-03-05T20:41:03 | 241,394,878 | 162 | 18 | NOASSERTION | 2022-06-18T19:16:22 | 2020-02-18T15:21:00 | R | UTF-8 | R | false | false | 2,648 | r | attribute_scrap.R |
# scraping attributes from HTML elements
#' Scraping attributes from HTML elements
#'
#' @description This function is used to scrape attributes from HTML elements
#'
#' @param link the link of the web page to scrape
#' @param node the HTML element to consider
#' @param attr the attribute to scrape
#' @param askRobo... |
6995476c7344bf43dc9986c237c5b6a64207f5e0 | 7b8478fa05b32da12634bbbe313ef78173a4004f | /man/desc.Rd | 59328fd4d2a15611055c4bb5411d3b7397966cfc | [] | no_license | jeblundell/multiplyr | 92d41b3679184cf1c3a637014846a92b2db5b8e2 | 079ece826fcb94425330f3bfb1edce125f7ee7d1 | refs/heads/develop | 2020-12-25T18:02:10.156393 | 2017-11-07T12:48:41 | 2017-11-07T12:48:41 | 58,939,162 | 4 | 1 | null | 2017-11-07T12:01:35 | 2016-05-16T14:30:38 | R | UTF-8 | R | false | true | 451 | rd | desc.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/util.R
\name{desc}
\alias{desc}
\title{Arrange specified column in descending order}
\usage{
desc(var)
}
\arguments{
\item{var}{Variable to arrange in descending order}
}
\description{
Arrange specified column in descending order
}
\examples{... |
3a3c5f472af46c9acf1ee9426def44be3bf751f1 | b528057b1cdf0d288405efa3ce0d42186191c7f0 | /plan_prep_trendchanges.R | ce9d062e5d31af5103b019eec37e52489379b376 | [] | no_license | sarcusa/4ka_steph | 6d909d7d73144099bf57ea7d68cca5fe3e14a160 | 4db07bd56edaba0eaeae3bc4c8a20a20756f6a59 | refs/heads/master | 2023-02-18T18:08:02.752606 | 2021-01-24T19:16:45 | 2021-01-24T19:16:45 | 281,261,458 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 735 | r | plan_prep_trendchanges.R | TrendChanges_prep1 <- function(input_data, input_param){
print("Start brocken stick function")
analysis_3a = BrokenStick(input_data, input_param)
out3a = {
datPath = file.path(createPaths(), 'RData', 'TrendChanges.RData')
save(analysis_3a, file = datPath)
}
print("completed brocken stick functio... |
f235dbf39bc33b615486cc45d4ea629eb3c52cfd | 7a0db46e0d8207d2e7cdb1447a2ed2029d97f47d | /R/class_fuzzycluster.R | 3455c071eb3474e318a2bfa8affd3f1923b71fb5 | [] | no_license | fauzipandya/advfclust | 726571a0436befde2482b2c2d002c41bd0711f14 | ebeaa97ce8ca4e8aeea10695b0ebb7c09ede25d6 | refs/heads/master | 2020-09-21T19:37:09.567968 | 2016-09-24T16:45:42 | 2016-09-24T16:45:42 | 66,117,846 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 881 | r | class_fuzzycluster.R | #' Fuzzy Result
#' @import methods
#' @name fuzzycluster-class
#' @rdname fuzzycluster-class
#' @slot centroid centroid matrix
#' @slot distance distance matrix
#' @slot func.obj function objective
#' @slot call.func called function
#' @slot fuzzyfier fuzzyness parameter
#' @slot method.fuzzy method of fuzzy clustering... |
06804f61a2ab51cee45e8eecf54121b51cff0daf | 2949cf3cb789a42eafa00ba74f04938ed9cb6af0 | /final version/train.R | c778a95d7582969babb659d41146c3d562418209 | [] | no_license | TZstatsADS/Fall2016-proj3-grp2 | 6611fdf0f9d2394d2754ccbea3c8101db85dd967 | 182a5c42254b83ac5e9259f61bda0fd76a327008 | refs/heads/master | 2021-05-01T04:33:27.680337 | 2016-11-02T21:13:53 | 2016-11-02T21:13:53 | 71,174,560 | 0 | 3 | null | null | null | null | UTF-8 | R | false | false | 3,187 | r | train.R | #########################################################
### Train a classification model with training images ###
#########################################################
### Author: Group 2
### Project 3
### ADS Fall 2016
train <- function(feature.adv, feature.baseline, label_train){
### Train a Gradient Boo... |
fbaf401dbcd34dbe8dd97ec383c5baa8b9e7c780 | a7961945baed475b1540ebc61a918a36159a5543 | /cachematrix.R | a7db79924be47d1284bf1e7f089cddf16393450b | [] | no_license | theodore-rice/ProgrammingAssignment2 | 7b0e36d5d0a35e121405d1c26d3a1012a54851b7 | d89bd3a12c2c32b1e3f3fd1e2361591074b9dc25 | refs/heads/master | 2020-12-07T13:44:55.022049 | 2015-06-13T00:51:29 | 2015-06-13T00:51:29 | 37,348,525 | 0 | 0 | null | 2015-06-12T22:58:17 | 2015-06-12T22:58:17 | null | UTF-8 | R | false | false | 1,192 | r | cachematrix.R | ## This pair of functions cache the inverse of a matrix, so that if the
## inverse is needed in subsequent computations, it does not need to be
## recomputed
## This creates a special matrix, which is really a list which
## 1) sets the value of the matrix
## 2) gets the value of the matrix
## 3) sets the value of the... |
744615c2fa274b79f2bff7500f057de05ff2c9bd | b5b43e544d901665cc2a2ff2518fff5b44d882a0 | /man/compare_title_paper.Rd | 248de1cb4464c44c54b97d4b3fa33354ff73207b | [] | no_license | jamielatham15/bibliographica | 14b894fb16403a22051903598fd2b443709fdb6d | 62bb9feb231c1d6b93960ced52404bcfb496252e | refs/heads/master | 2021-01-23T01:51:17.343584 | 2017-03-03T11:14:56 | 2017-03-03T11:14:56 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 778 | rd | compare_title_paper.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/compare_title_paper.R
\name{compare_title_paper}
\alias{compare_title_paper}
\title{Compare Title Count and Paper Consumption}
\usage{
compare_title_paper(x, field, selected = NULL, plot.mode = "text")
}
\arguments{
\item{x}{data frame}
\ite... |
edb6e26fc6f15ebcea0a3bfc8f509059e44b2072 | edaca2016899ea5755eef108898e05223a6094ff | /TempModelFunctions.R | 2ad8625a4822c9af60a42ae685ded20d101aad73 | [] | no_license | DCBraun/Temperature-Modelling | e2a9464c9e8bbdc7031c46c673d22dd08a2365ec | cf4e1519bcd1eed304ca776a59e1789556be0928 | refs/heads/master | 2020-04-09T18:37:11.255255 | 2015-02-06T23:14:16 | 2015-02-06T23:14:16 | 31,793,340 | 0 | 1 | null | 2015-03-06T23:11:03 | 2015-03-06T23:11:02 | null | UTF-8 | R | false | false | 3,148 | r | TempModelFunctions.R | ############################
# TempModelFunctions.R
# Project: TemperatureModelling
# File for the functions that appear in the temperature modelling files
# Not all of these functions are currently used in the TempModel.r code
# Some were used and have since been removed, others were created but never used.
# Create... |
5cd1fbefd051c508e9bd2d42f81680341b347eb0 | e5e7b46cb9bcf6954614d52bba8e1408b175c000 | /plot4.R | 7bef02af773d49af32530b10f38106854be25702 | [] | no_license | MariaMontesdeOca/ExData_PA1 | 596d6198ea59f984ff076fdb759617d080661f98 | 1be0a18c662c6daa7aac88bba4d97ff45689bba6 | refs/heads/master | 2020-06-04T16:52:02.780131 | 2015-04-12T12:12:58 | 2015-04-12T12:12:58 | 33,812,540 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,537 | r | plot4.R | #Read the data into R
data<-read.table("household_power_consumption.txt",sep=";",header=TRUE,colClasses=c(rep("character",2),rep("numeric",7)),na="?")
#Convierte Date en formato fecha
data$Date<-as.Date(data$Date,"%d/%m/%Y")
#Select only the dates that we're gonna plot
refineddata<-subset(data,Date=="2007-02-02"|Dat... |
6f94b0a18304420dcc680aea2864e1f8350e09b6 | 08b7728c2120413ad2266a5e7ae3403e6b67471b | /cryptoJNS/man/affineCipher.Rd | 94b2e006bc8ab923af821101f2be1e6ceee80587 | [] | no_license | JamesSolum/Codes-and-Encryption | 8241438fa8fa6c1e36ecfc293d6c1bf02cc3f36b | 59df5d2ca7505795bd876db2b532351a28a9a122 | refs/heads/master | 2020-05-29T21:04:36.541728 | 2017-02-21T00:09:00 | 2017-02-21T00:09:00 | 82,615,292 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 755 | rd | affineCipher.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/affineCipher.R
\name{affineCipher}
\alias{affineCipher}
\title{Encrypt a string using a shift cipher}
\usage{
affineCipher(plainText, stretch, shift)
}
\arguments{
\item{plainText}{A string of lowercase letters}
\item{stretch}{An integer use... |
9d2a2a8d5295fc3a7b39b614271bca5b98fa8fa9 | 6037c26c14d146cd9bcaf612eea52aeec10d48d1 | /man/merge.Rd | 39a281d83e8ecc8be6021bf4303655f63c33dce7 | [
"MIT"
] | permissive | HaidYi/DASC | ed1860cb63d1ddb039e7f1a727cc65e4f71e3e12 | 5f36f7aa02d810be0acde2f90efafbb116d9affb | refs/heads/master | 2021-01-18T17:50:31.758972 | 2018-06-01T09:00:36 | 2018-06-01T09:00:36 | 114,265,991 | 5 | 1 | null | null | null | null | UTF-8 | R | false | true | 795 | rd | merge.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/DASC.R
\name{merge}
\alias{merge}
\title{Combine two trees into one}
\usage{
merge(x, y, X)
}
\arguments{
\item{x}{the index of the node}
\item{y}{the index of the node}
\item{X}{the saved vector with the information of the parent of every ... |
9a08eb9af0d49467f25cd0e0c8dfe87c0ad9d5db | 3a0f2d5f03f7b196b86793938c1d892d629cac70 | /database/data/2016/player-stats/wk1-12/16_playerJoin.R | d4fe9f3ef4f2cbee97d25345a5711adf0de55e65 | [] | no_license | designer-citrusbits/Fantasy-Football-Database | db80d2e7bd5d6f6dc590fe0c5df5e4895bfcc0d7 | 0bc1343432cb8e89f8be7dc2932d6c57cf4f3fa9 | refs/heads/master | 2020-04-19T23:36:06.673291 | 2017-03-31T17:18:48 | 2017-03-31T17:18:48 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,581 | r | 16_playerJoin.R | # File: 16_playerJoin.R
# Description: combines multiple player csv's into one
# Date: 1 December 2016
# Author: Mark Eidsaune
library("RCurl")
library("plyr")
library("dplyr")
durl <- "https://raw.githubusercontent.com/edavis25/Fantasy-Football-Database/master/database/data/2016/player-stats/wk1-12/11-29-2016-defens... |
593d86a70e6a377b0a56d38be9439ead1b3cb4a5 | 375250017804497a9830ad9244a9a4140f9dccef | /inversion/deprecated/inversion_ps.multiPFT.US-WCr.multivariate.prior.R | 531eb2606685f88344103aa16efbf6605ce2d2da | [] | no_license | serbinsh/edr-da | 21d0aa8f45622707443a60fa5845fc5ef4e8b722 | 462ffc9104532b94139c072c59aad5b2383cda1e | refs/heads/multi-pft | 2021-01-12T13:12:36.735625 | 2017-10-03T21:33:54 | 2017-10-03T21:33:54 | 72,149,480 | 2 | 0 | null | 2017-10-03T21:33:55 | 2016-10-27T21:24:19 | R | UTF-8 | R | false | false | 10,404 | r | inversion_ps.multiPFT.US-WCr.multivariate.prior.R | #--------------------------------------------------------------------------------------------------#
#
#
# S. Serbin & A. Shiklomanov
#--------------------------------------------------------------------------------------------------#
#---------------- Close all devices and delete all variables. ---------------------... |
b327594281849146e551e25b8eb18f4fe44f5d4e | cdccaa7a602c7d61108abdbb27833d33376e6fca | /R 프로그래밍 기초/R Basic(3) - String Function.R | 40204e44108e388a388e57b51c8d8af9248c9c54 | [] | no_license | JEONSUN/Jeon-S_R | 0509766421d1cc747754d7bf9315964a01978b5a | 8053ce8a29b4abe78827cbea587f13d09a25613e | refs/heads/master | 2020-08-10T18:58:31.910324 | 2020-06-28T17:22:19 | 2020-06-28T17:22:19 | 214,401,217 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,796 | r | R Basic(3) - String Function.R | # 문자열을 위한 함수
# 함수 nchar() : 문자열을 구성하고 있는 문자 개수
x <- c('park','lee','kwon')
nchar(x)
# 한글도 글자수를 셈
nchar('응용통계학과')
#########################
# 함수 paste(): 문자열의 결합
#옵션 sep의 활용
paste('모든','사람에게는','통계적','사고능력이','필요하다')
paste('모든','사람에게는','통계적','사고능력이','필요하다',
sep = '-')
paste('모든','사람에게는','통계적','사고능력이','필요하다',
... |
0c85a1a14f7124da617310c9acecd9e3bb7a2f9b | b9ee91175c4115fea52323a8e4019be9d44bd2e5 | /ISLR/random_forest_class.R | 171550d1d19af5626a2719b9b907b439d7a0ff1d | [] | no_license | creyesp/r-course | c50ec510262c4e7e6c55a0b12395c22df67cf923 | f8bc8b99a466baf733080b16ee5cac20ff118c6d | refs/heads/master | 2023-04-10T15:54:10.910664 | 2020-12-09T00:16:26 | 2020-12-09T00:16:26 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,835 | r | random_forest_class.R | # https://cran.r-project.org/web/packages/randomForest/randomForest.pdf
#
# install.packages('randomForest')
# install.packages("caret")
# install.packages("e1071")
# install.packages("doParallel")
library(caret)
library(e1071)
library(doParallel)
library(dplyr)
library(randomForest)
# library(doMC)
# registerDoMC(... |
65ae08d8bac45fdd41f7523d0112c5cedcd2f12f | 584c1168097d5939f5c2f9cefbd1aab3767b5b7b | /AleatoriosShiny.R | 79b88a88495617ac70f549f8305617b9c57b4fd0 | [] | no_license | erikonchis/AleatoriosShiny | 7b9f99c8087805a214ea12c9b98da7b2216aea69 | 4689a9734e699bd2973b6b69640d2edda56475c6 | refs/heads/master | 2016-08-11T07:11:13.155904 | 2016-02-26T18:21:46 | 2016-02-26T18:21:46 | 51,943,718 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 342 | r | AleatoriosShiny.R | library (shiny)
ui <- fluidPage(
titlePanel("Genera y grafica números aleatorios"),
actionButton(inputId = "clicks", label="Genera datos"),
plotOutput("grafica")
)
server <- function(input, output){
datos <- eventReactive(input$clicks, {rnorm(100)})
output$grafica <- renderPlot({plot(datos())})
}
shinyApp(u... |
d9a6a6e487e04e7562f75cc807c4f327f89b1051 | 2527964c2e0e5391667b665e2f291e2d179ead94 | /R/CompressedDataFrameList-class.R | c330f0b1f55734d349e598bdc473ec5cb17e2ad2 | [] | no_license | Bioconductor/IRanges | c5d2e040c59b6b35ca5355e31a300327f057acba | 2a45618f740681086b8ff9d5064cbafd5bfd2113 | refs/heads/devel | 2023-07-10T00:02:55.299599 | 2023-06-22T02:44:53 | 2023-06-22T02:44:53 | 101,238,649 | 18 | 19 | null | 2023-06-13T19:15:31 | 2017-08-24T01:02:36 | R | UTF-8 | R | false | false | 5,550 | r | CompressedDataFrameList-class.R | ### =========================================================================
### CompressedDataFrameList objects
### -------------------------------------------------------------------------
setClass("CompressedDataFrameList",
contains=c("DataFrameList", "CompressedList"),
representation("VIRTUAL", unlistDat... |
3235190c0d45566aab159aab975703816ba2d0fb | 4b08dfacf916de2bf5ef0ce4a0d2040b70946794 | /R/desolve.R | a4d83f39eb1aa059a3ab16f31b456b6530b1a652 | [] | no_license | richfitz/diversitree | 7426e13415829e3fc6a37265926a36461d458cc6 | 8869a002f8c978883f5027254f6fbc00ccfa8443 | refs/heads/master | 2023-08-08T23:13:59.081736 | 2023-05-03T14:43:17 | 2023-05-03T14:43:17 | 3,779,673 | 16 | 13 | null | 2023-08-24T14:46:37 | 2012-03-20T20:29:11 | R | UTF-8 | R | false | false | 726 | r | desolve.R | lsoda.trim <- function(...) {
ret <- t(lsoda(...)[-1,-1,drop=FALSE])
dimnames(ret) <- NULL
ret
}
## This sets things up the way that deSolve likes them
derivs.for.deSolve <- function(f)
function(...) list(f(...))
make.ode.deSolve <- function(info, control) {
if ( !is.function(info$derivs) )
stop("info$d... |
d389642d6a247046b93f3932bdbae5d2f72555fb | 49ff0bc7c07087584b907d08e68d398e7293d910 | /mbg/mbg_core_code/mbg_central/LBDCore/tests/testthat.R | 042278b66566b1d93f7f085faa18deff4f23d617 | [] | no_license | The-Oxford-GBD-group/typhi_paratyphi_modelling_code | db7963836c9ce9cec3ca8da3a4645c4203bf1352 | 4219ee6b1fb122c9706078e03dd1831f24bdaa04 | refs/heads/master | 2023-07-30T07:05:28.802523 | 2021-09-27T12:11:17 | 2021-09-27T12:11:17 | 297,317,048 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 91 | r | testthat.R | library(testthat)
library(LBDCore)
singularity_version <- "default"
test_check("LBDCore")
|
01ed5600bdb454a97c4bdc647a2989f13295804e | f94c4b201a378fa7a14e9f88d3004b755b022ead | /ExtraPackages/linus/stock.Analyze/man/get.script.name.Rd | 6bf599de39c83bc90ffc3d3a67bb99b93f7ab50a | [] | no_license | linushsao/Analysis.of.trading.strategies | 5b9b58f90582ad98eedf0946d18be9d66bcc069b | 6af5730b7c9cc5d10a1002b9709fba855b095d2a | refs/heads/master | 2021-11-10T19:38:02.399402 | 2021-11-07T09:16:18 | 2021-11-07T09:16:18 | 251,311,218 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 371 | rd | get.script.name.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/m_get.script.name.R
\name{get.script.name}
\alias{get.script.name}
\title{A get.script.name Function}
\usage{
get.script.name()
}
\arguments{
\item{x}{A numeric vector.}
}
\description{
This function allows you to multi paste vector.
}
\examp... |
987a0955ac87b4c608840dce3f6e4b1c6c3c1d81 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/SixSigma/examples/ss.data.pb1.Rd.R | 2ce29b542c4b71544360a42db61856f0f998258d | [] | 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 | 376 | r | ss.data.pb1.Rd.R | library(SixSigma)
### Name: ss.data.pb1
### Title: Particle Boards Example - Individual Data
### Aliases: ss.data.pb1
### Keywords: cc data
### ** Examples
data(ss.data.pb1)
summary(ss.data.pb1)
library(qcc)
pb.groups.one <- with(ss.data.pb1, qcc.groups(pb.humidity, pb.group))
pb.xbar.one <- qcc(pb.groups.one, type... |
75511777f011a87873a3fd330c54d6d586b5a6ab | b3a1025e9ec447064e0bec82630e261acb5a2949 | /src/plot_figures.r | 488d72f3e3feabedbe718e9016a8b455a2a78656 | [] | no_license | schlogl2017/rates_measurement | 0f80ad0df55be53358dacaaa9bd5b64b70f32c15 | c05cc3a4a7e31c03bfe77c69e50a2ffbb6a545b4 | refs/heads/master | 2022-11-20T07:05:26.628270 | 2018-09-11T19:59:02 | 2018-09-11T19:59:02 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,549 | r | plot_figures.r | library(tidyr)
library(ggplot2)
library(dplyr)
library(cowplot)
library(readr)
####Figure: Analytically derived rate and inferred rate when true model is MutSel and inference model is JC#####
r_an <- read_csv("../analytical_rates/ten_sites_aa.csv")
r_inf<- read_csv("../inferred_rates/processed_rates/rates_ten_sites_aa... |
9a8bd3062355f142cc34588d4c7c16411b4dd11c | 0b1e134538b514ba9c0aed8f4f4dc70d719a847b | /man/print-methods.Rd | 9d3ea54df6b4c136b2a7f67dbf19fcce7a8bddf3 | [] | no_license | cran/ppmlasso | e6ed9e8b6b6190b2bf7ddc38108213aa6f667495 | 1a0ebbb5ea95088c6d639e6f034c452786dd9445 | refs/heads/master | 2022-12-18T09:59:20.444663 | 2022-12-01T11:50:02 | 2022-12-01T11:50:02 | 17,698,696 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 429 | rd | print-methods.Rd | \name{print-methods}
\docType{methods}
\alias{print-methods}
\alias{print,ppmlasso-method}
\title{Methods for function \code{print}}
\description{
Methods for function \code{\link{print}}
}
\section{Methods}{
\describe{
\item{\code{signature(x = "ppmlasso")}}{
Prints output for a \code{ppmlasso} object wit... |
57f65942ad9f35bcfa7ca978826bb61b24a7d6b1 | cedee53b1bdaf0d70fc83cf6d13ea2aa0897f295 | /RandVarGen/server.R | fe132b86c858fc3a3bfe8e4af35312aea6628230 | [
"MIT"
] | permissive | awstown/shiny1 | b12a892278b4980ceca293dc408f61642d22de75 | 62e2f54120aa4a3b75fc16da09999cec3c361947 | refs/heads/master | 2021-09-22T16:06:45.337636 | 2018-09-11T19:25:11 | 2018-09-11T19:25:11 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,399 | r | server.R | library(shiny)
source("rvg.R")
shinyServer(function(input, output) {
#######################################
# Probability Integral Transform
#
# Exponential Example
exp.all.out<-reactiveValues()
observe({
if(input$go.exp==0){exp.all.out$history<-init.all()}
else{
exp.all.out$history<-add.exp(iso... |
41bd7b09525be138478311dd96e52a1a79f96712 | c5087b724353b127d69bca2eff5b62aa600a71b8 | /R/pad-trim.r | 466e21f0f00de189569a568eb40c58232b8b1d81 | [] | no_license | hyiltiz/stringr | 9e0793655827c60f5f5e9ee470a2e35ffe0e94a6 | 82c4235354deec2338ef636ce604fab01c4338cc | refs/heads/master | 2020-12-11T03:25:34.074649 | 2015-03-31T13:11:31 | 2015-03-31T13:11:31 | 33,868,168 | 1 | 0 | null | 2015-04-13T12:49:15 | 2015-04-13T12:49:15 | null | UTF-8 | R | false | false | 1,691 | r | pad-trim.r | #' Pad a string.
#'
#' Vectorised over \code{string}, \code{width} and \code{pad}.
#'
#' @param string A character vector.
#' @param width Minimum width of padded strings.
#' @param side Side on which padding character is added (left, right or both).
#' @param pad Single padding character (default is a space).
#' @retu... |
03e548e7cc9cea51d4f80a7eb30c7bae2ee8d30a | 93819d8d464369f0036a61a35358c20108755ff9 | /code/working/makedata_partitions.R | 8c735e709ca8e21f6d4f73724345040d99bf44e1 | [
"MIT",
"CC-BY-4.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-public-domain"
] | permissive | jdblischak/fucci-seq | 3606074f6fd901509140d48bc847934af52aa4c8 | de244c3247d225b8886ec778c7063a9fb2731e30 | refs/heads/master | 2022-01-21T09:20:38.761518 | 2022-01-06T20:04:30 | 2022-01-06T20:04:30 | 72,239,601 | 7 | 5 | NOASSERTION | 2019-09-17T15:36:03 | 2016-10-28T20:25:18 | R | UTF-8 | R | false | false | 3,754 | r | makedata_partitions.R | ################################################
# Description:
# Partition samples to training and validation
################################################
library(Biobase)
df <- readRDS(file="data/eset-final.rds")
pdata <- pData(df)
fdata <- fData(df)
# select endogeneous genes
counts <- exprs(df)[grep("ENSG",... |
50475107245fe689f0b24e1b4973fcf5fa610e5a | 49ff0bc7c07087584b907d08e68d398e7293d910 | /mbg/mbg_core_code/mbg_central/LBDCore/R/save_custom_raking_outputs.R | ab234ab25c48394ab475f8519a5a39fcb67a346f | [] | no_license | The-Oxford-GBD-group/typhi_paratyphi_modelling_code | db7963836c9ce9cec3ca8da3a4645c4203bf1352 | 4219ee6b1fb122c9706078e03dd1831f24bdaa04 | refs/heads/master | 2023-07-30T07:05:28.802523 | 2021-09-27T12:11:17 | 2021-09-27T12:11:17 | 297,317,048 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,313 | r | save_custom_raking_outputs.R | #' @title Save outputs from custom raking function
#' @description This function saves outputs from \code{custom_rake}
#'
#' @param custom_rake_output Output list from custom raking function
#' @param outdir Directory for files to be saved to
#' @param indicator Name of indicator being modeled
#' @param age_group Name ... |
1b6c555c96ec40b6e96f5244656ba8e00cd2fcb3 | 739e57abf7c1723a655c31616dbeead52cd423d5 | /analysis/sequential/model/kmcox_combine.R | fd0e48fa26e6c00965317882d3d8be151cddb2e5 | [
"MIT"
] | permissive | opensafely/covid-vaccine-effectiveness-sequential-vs-single | d6dde4b62ebec8f2bb8844e148efe06dd44adc1b | 46c1314fe25b17d3e04d355e832e853b1464b531 | refs/heads/main | 2023-08-23T10:42:13.962541 | 2023-02-20T16:59:22 | 2023-02-20T16:59:22 | 588,559,908 | 3 | 0 | MIT | 2023-05-16T16:40:35 | 2023-01-13T12:22:53 | R | UTF-8 | R | false | false | 2,308 | r | kmcox_combine.R | # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# Purpose: Combine km estimates from different outcomes
# - The script must be accompanied by three arguments:
# `brand` - the brand used
# `subgroup` - the subgroup variable
# `outcome` - the outcome variable
# # # # # # # # # #... |
8771bdc950da76300abaf80f3ec581437ef9b91f | 9947a34b5354c41cb4998e761062f8d82f566b6b | /Core_manuscript/Pinechrom/Scripts/run_deseq2_atac.R | a6a9762caeced67bdba0f621f391e304e0f30b0d | [] | no_license | jknightlab/ATACseq_pipeline | 4f3935576e23d36d880116190f3ab63b86537ded | 7a30e39a87eaa7cb583a414b7661497886fa8199 | refs/heads/master | 2020-12-07T17:10:17.748148 | 2016-09-28T18:53:16 | 2016-09-28T18:53:16 | 46,871,204 | 5 | 4 | null | null | null | null | UTF-8 | R | false | false | 4,285 | r | run_deseq2_atac.R | library(DESeq2)
args<-commandArgs(TRUE)
input_counts <- args[1]
input_colnames <- args[2]
output_header <- args[3]
# Generating filenames
filename_count_table <- paste(output_header, ".normalized_counts.txt", sep="")
filename_de_plots <- paste(output_header, ".DE_plots.pdf", sep="")
filename_de_results <- paste(outp... |
7b58f9c8f4fb380de36d5ada70d80dc7e233d757 | b68f6f88ee633d16bd6d116ab4cdcb8fae1849d9 | /RGuide/Chapter 4_6.R | 3f0503b6c38a4120a865a9125cad7893e7f25621 | [
"MIT"
] | permissive | HealthyUncertainty/healthyuncertainty.github.io | 9a6bc9279fa064a4b368923ba131a3ac9212ea2d | 8546fb628da98640c29e268466273ef970530d4c | refs/heads/master | 2023-04-01T12:31:43.422831 | 2021-04-03T01:28:15 | 2021-04-03T01:28:15 | 314,864,416 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,984 | r | Chapter 4_6.R | #####################################################################################
# #
# TITLE: Building Health State Transition Models in R: Chapter 9 #
# ... |
314b796df07259051c67eda6471b9377c8d9db89 | 09e288ff4c1637e4e1501d3283bb7cabc6d62eba | /diaryRepository.R | 64273d23fe6bfe05f0613e843ab6117e3e890a64 | [] | no_license | vika95viktoria/Diary-in-R | 68d8c8b73fe8d71fc56ed8e28264055b57ba7a27 | aeb85a98f00347042d1b7391299c5333d4159c9b | refs/heads/main | 2023-01-11T10:47:13.008069 | 2020-11-15T12:15:10 | 2020-11-15T12:15:10 | 313,022,037 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,213 | r | diaryRepository.R | library(RPostgreSQL)
library(DBI)
library(stringr)
pw<- {
"test123"
}
get_connection <- function() {
con <-dbConnect(dbDriver("PostgreSQL"),
dbname="diary",
host="host.docker.internal",
port=5432,
user="test_user",
password=p... |
e9799af14a0aa7228fa51afbabc1afec80079b86 | 7fd895918aa4c54b619c3fe7ea8a2171d0b9e585 | /man/bal.tab.matchit.Rd | f713340cac08a89c3212b443be3f9537f1d821e0 | [] | no_license | EvaMaeRey/cobalt | 15a6d580bfd5c0383bfab972f7516cd2439bc086 | 82c3c71736911702534311db4a47beaa8ccd9e46 | refs/heads/master | 2020-03-16T08:32:39.644168 | 2018-05-08T11:40:51 | 2018-05-08T11:40:51 | 132,597,911 | 1 | 0 | null | 2018-05-08T11:16:31 | 2018-05-08T11:16:31 | null | UTF-8 | R | false | false | 7,323 | rd | bal.tab.matchit.Rd | \name{bal.tab.matchit}
\alias{bal.tab.matchit}
\title{
Balance Statistics for Matchit Objects
}
\description{
Generates balance statistics for \code{matchit} objects from \pkg{MatchIt}.
}
\usage{
\method{bal.tab}{matchit}(m,
int = FALSE,
distance = NULL,
addl = NULL,
data = NULL,
continuous = c... |
55077a49221b294fbee65c861470d1ffb9c6ad7a | 3410f4f90f0e431bf3a6105d8ea73215c548066f | /outcome.R | 2111bdce2b7827e94e7d9c8828b88df862581ba5 | [] | no_license | jhonatansgg/Final-project | 6ecb550e9aad285097efa7dada26855a15587e40 | 1c9a9dbd7fc2b283209a6812ada0cf6b4c2597f8 | refs/heads/master | 2022-12-03T18:04:45.693629 | 2020-08-07T05:01:57 | 2020-08-07T05:01:57 | 285,741,190 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 317 | r | outcome.R | outcome <- read.csv("outcome-of-care-measures.csv",colClasses = "character")
head(outcome)
ncol(outcome)
nrow(outcome)
names(outcome)
outcome[,11] <- as.numeric(outcome[,11])
hist(outcome[,11],xlab = "Muertes",main = "Tasas De Mortalidad Hospitalarias De 30 Dias(Al Mes) Por Ataque Cardiaco"
,col = "lightblue")
|
ced435b31ea3f1e726db9a992a950e0178a2b9b2 | a14a124c6901ad11bb21b5742ecce3052aad9aba | /man/fun_logic_assg.Rd | 1b1df74cd8c8921d5990e003f1b492a35ea8e95b | [] | no_license | DataCollaborativeForJustice/mjp | 8ecde44e11227aaf429b5f84adb4b5d3567bd4a3 | f9d7ae05a58a3c28cc22e5ae40aa8226ac158014 | refs/heads/master | 2022-03-13T13:10:13.742983 | 2019-09-23T13:50:18 | 2019-09-23T13:50:18 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,132 | rd | fun_logic_assg.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fun_logic_assg.r
\name{fun_logic_assg}
\alias{fun_logic_assg}
\title{Logical assignment, a MJP team defined function}
\usage{
fun_logic_assg(x, reference, typo_col = "TYPO", replace_col = "REPLACEMENT")
}
\arguments{
\item{x}{A input variable... |
e73d24ae591648c8692d11810f7e9d4a6c001fea | c58a1595115fea554db8cd6578279f574eabfa0e | /man/chk_names_complete.Rd | 98dea08e6465e6827a006959a9fddbdeae8f2aa7 | [
"MIT"
] | permissive | bayesiandemography/demcheck | 129aca86fecda02be83bea73e639fb45d366c651 | c52c3e4201e54ead631e587ebf94f97f9c7a05a0 | refs/heads/master | 2021-12-28T15:40:54.771894 | 2021-12-17T03:10:50 | 2021-12-17T03:10:50 | 200,993,678 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 716 | rd | chk_names_complete.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/chk-composite.R, R/err-composite.R
\name{chk_names_complete}
\alias{chk_names_complete}
\alias{err_names_complete}
\title{Check that an object has a complete set of names}
\usage{
chk_names_complete(x, name)
err_names_complete(x, name)
}
\ar... |
6f96970180cd7fe8aa85b2b71ab8652369a72df7 | 40bbc7902204805f6975d62d15bffb433ad8d572 | /cleaning.R | d02999d59c0adfe73a8636ce1ad8aa62f3b288b4 | [] | no_license | simon00001/capstone | 4cb645fea2c30caf2e65352cab3e4041085bfc6a | b5f10042d4ba1e1ccb0598adfd322c16cad493ab | refs/heads/master | 2016-09-13T15:02:47.929905 | 2016-04-25T03:57:33 | 2016-04-25T03:57:33 | 57,006,059 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,635 | r | cleaning.R | # This is module for a Shiny web application.
#
# Application : Word Prediction module
# by : Simon Kong
# date : 21 Apr 2016
suppressPackageStartupMessages(c(
library(shiny),
library(tm),
library(stylo),
library(stringr)))
# Loading N-gram for bi, tri and ... |
1378aaf0c7a3ca369e4818e5147a1c4989b42d43 | 5fd3ddd30766a4eae04069b44bfe4f85f9dfaa40 | /R/getNHINoBasedOnRCFNo.R | 55c3850a61d37f96c18d46722bbf92b5d8ef36bb | [] | no_license | Angelacheese/pharm | 1a18155194cbc6551f12e28083f2a01a347dd0fb | 9f7d600752641edb30353f4575d89a9db6cc67ab | refs/heads/master | 2022-10-06T03:13:18.425075 | 2019-07-18T08:09:56 | 2019-07-18T08:09:56 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 590 | r | getNHINoBasedOnRCFNo.R | #' Get NHINO based on RCFNO
#'
#' @import dplyr
#' @param df data.frame include RCFNO
#' @param RCFNoColName A colum for RCFNo of df
#' @export
get.NHINoViaRCFNo <- function(df, RCFNoColName = RCFNO){
colnames(df)[colnames(df)==deparse(substitute(RCFNoColName))] <- "RCFNO1"
NHINoData <- df %>% select(RCFNO1) %>%... |
7a9547f37a67fe18c408ebdcdb85ea1b66dbd066 | 319a13e48a7e26e5ab660c9dba30521834203dab | /RFiles/arma.R | 23a7bdf8d4b1c810264a588ec49f91c1d8963981 | [] | no_license | marco-tn/StaticticsBasic | 9b4914bec56571754b54481e53f389654178cb3b | 6dba8d4ac01759cd1e7af302386b9a34f3594475 | refs/heads/master | 2020-08-03T13:06:57.357421 | 2019-09-30T03:00:07 | 2019-09-30T03:00:07 | 211,762,589 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 502 | r | arma.R | ## ARMA(2,1)モデルのシミュレーション
n <- 1000
a <- c(0.8, -0.64) # AR の係数
b <- -0.5 # MA の係数
# for文で生成
epsilon <- rnorm(n)
x0 <- rnorm(2) # 初期値を乱数で指定
x <- ts(double(n))
x[1:2] <- x0
for(i in 3:n) x[i] <- a %*% x[i - 1:2] + b*epsilon[i-1] + epsilon[i]
plot(x)
# arima.simで生成する方法(初期値の指定は出来ない)
# 関数arma.simのノイズはデフォルトでは標準正規列
y <- arima... |
d4a2fe2b4f4068ef6aedcaac7574a3aecffbf338 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/pastecs/examples/decloess.Rd.R | 8187ea96fb2d38b38ab1e54542b650907df31dc3 | [] | 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 | 461 | r | decloess.Rd.R | library(pastecs)
### Name: decloess
### Title: Time series decomposition by the LOESS method
### Aliases: decloess
### Keywords: ts smooth
### ** Examples
data(releve)
melo.regy <- regul(releve$Day, releve$Melosul, xmin=9, n=87,
units="daystoyears", frequency=24, tol=2.2, methods="linear",
datemin="... |
7b8a0b48593b3cafebbf1afb236290bb5835e65e | 85b850779b0e241cc4e1bfe0c3cae7304f0e1102 | /ui.r | b8640045ff25fb10270af9439ae07af97762df4a | [] | no_license | NikhilSinghChandel/CodeTheGame-IITBombay-Final | aa004ba574bb08c4e675bf78f152daf72d095c2c | 2db119ac74f659eb4a346387b6c4e68320846e99 | refs/heads/master | 2020-03-22T10:27:32.444988 | 2018-07-05T21:51:37 | 2018-07-05T21:51:37 | 139,903,822 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 489 | r | ui.r | library(shiny)
shinyUI(pageWithSidebar(
headerPanel("Code the Game"),
sidebarPanel(
fileInput('file1', 'Choose CSV File',
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv')),
tags$hr(),
fileInput('file2', 'Choose CSV File',
accept=c('text/csv', '... |
58c977ea7e74827adf6d7f4a1fc6fd9242eb0127 | 039881b907d13512a8e5ca551aba51a739aa7a7e | /R/tm1_get_dimension_elements.R | 6a4aab9c191a9319dd7eb942153c193d9d4e008e | [] | no_license | catgopal/tm1r | 0276bc7df03f0071addcaa09ec5820772f7b0905 | 679b5a556b8ab3e7b4befa238372d0e16a8707ca | refs/heads/master | 2021-09-28T14:06:26.750075 | 2018-11-17T21:33:55 | 2018-11-17T21:33:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,574 | r | tm1_get_dimension_elements.R | tm1_get_dimension_elements <- function(tm1_connection, dimension) {
tm1_adminhost <- tm1_connection$adminhost
tm1_httpport <- tm1_connection$port
tm1_auth_key <- tm1_connection$key
tm1_ssl <- tm1_connection$ssl
# added because some http does not know space
dimension <- gsub(" ", "%20", dimension, ... |
00d068cda51410851b766889a4dc2245730c72f9 | 21da3f5a064c26741a0f3667c1e3f864e35c5874 | /Map-Making-USA/mini_project-2_1999.R | 8a11e470e4fd412de8707b21d078951bcbc81d38 | [] | no_license | divyanshu93/Implementation-of-Statistical-Methods | d30f3ced4283e716cb4bec8f4ccd066d6ecac6e0 | 8a78e56bde30f296454e09704d61fe18c5ca308d | refs/heads/master | 2021-01-17T18:35:32.917009 | 2016-06-06T00:17:56 | 2016-06-06T00:17:56 | 60,486,735 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,436 | r | mini_project-2_1999.R | usa.df<-map_data("state")
str(usa.df)
colnames(usa.df)[5]<-"state"
usa.df$state<-as.factor(usa.df$state)
str(usa.df)
usa.dat <- read.table("/home/div/Documents/Frank_top_2012.csv", header = T, sep = ",")
str(usa.dat)
usa.df <- join(usa.df, usa.dat, by = "state", type = "inner")
str(usa.df)
usa.df = usa.df[usa.df$year==... |
5ccd9e9bf0b741d1c5003951a9ee6e5e185c97cb | 55a6299959d29fb2dccb55b6ee70d8b495e69bd4 | /R/cubinfAM.R | 2dab224b95824a48b85ca3fc585066de1bac77b4 | [] | no_license | cran/robcbi | 0b56c104b729378c1f5fda9ea15838861543e653 | be190c9343a869ef7c4855fcbac559442d57ed87 | refs/heads/master | 2020-03-13T20:51:04.996148 | 2019-07-23T14:00:05 | 2019-07-23T14:00:05 | 131,283,133 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 14,767 | r | cubinfAM.R | cubinf.control <- function(tlo = 0.001, tua = 1.e-06, mxx = 30, mxt = 10, mxf = 10 ,
ntm = 0, gma = 1, iug = 1, ipo = 1, ilg = 2, icn = 1, icv = 1,
ufact=0, cpar=1.5, null.dev = TRUE, ...)
{list(tlo = tlo, tua = tua, mxx = mxx, mxt = mxt, mxf = mxf,
ntm = ntm, gma = gma, iug=i... |
b0adec19e18cc3367ef0cc94107ceadc3ed0181d | d191f64fc6fbe26d7927e1b1fc69d6015eb57e79 | /ForecastContestExample.R | 638afa9b2d0b3091759ac977773407f27412ebcd | [] | no_license | XQ2013/Forcast-R-Example | 6ba6c54322fb7179ecfdec1b124cb0e3172e9d20 | 240a4feb34186602bc514d6625ceb6477a3ef805 | refs/heads/master | 2020-07-01T21:15:45.191004 | 2019-10-01T18:07:56 | 2019-10-01T18:07:56 | 201,303,379 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,842 | r | ForecastContestExample.R |
# Load the raw training data and replace missing values with NA
donations<- read.csv('donations.csv',header=T,na.strings=c(""))
donations <- donations[,-c(1,18)]
# Output the number of missing values for each column
sapply(donations,function(x) sum(is.na(x)))
# Quick check for how many different values for... |
8ab15d63403f01018eea82354a47fe1a69a06217 | b3b3a690ac233a93732ad3e73a2ee64c1c4a756c | /man/alnum.Rd | eced767cf789122daf51105107fdd954dd75ef62 | [] | no_license | kcf-jackson/combinatorParser | f707de5da1905a43cccd269007e55ed3b4f3fa6b | 25182c466fbadc11f832823c01e9773032c6ea2f | refs/heads/master | 2020-04-07T19:20:07.547755 | 2019-04-15T19:12:45 | 2019-04-15T19:12:45 | 158,644,538 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 286 | rd | alnum.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/character_classes.R
\docType{data}
\name{alnum}
\alias{alnum}
\title{Alpha-numeric}
\format{An object of class \code{character} of length 62.}
\usage{
alnum
}
\description{
Alpha-numeric
}
\keyword{datasets}
|
db09c045ffff3a89ff4c077944008e823c354d7b | a3a3a26d0ef80fba3d5c133d62e649dd55937f2c | /tests/testthat/test_polydata.R | e0a52645f0d7410544b2e9539c89631a24c6e219 | [
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-public-domain-disclaimer"
] | permissive | dblodgett-usgs/NCDFSG | 74181ab2d24d588072cf0add71f67141c5c48f14 | ec92886d9da885125fd08a059312ca2c3d86c465 | refs/heads/master | 2021-01-19T00:18:01.959465 | 2017-04-07T00:50:41 | 2017-04-07T00:50:41 | 73,005,025 | 1 | 1 | null | 2017-03-25T14:29:45 | 2016-11-06T16:53:21 | R | UTF-8 | R | false | false | 3,221 | r | test_polydata.R | library("ncdf4")
context("NCDF SG polygonData tests")
# data prep.
# library(rgdal)
# shapeData<-readOGR(dsn = "data/Yahara_alb/Yahara_River_HRUs_alb_eq.shp",
# layer = "Yahara_River_HRUs_alb_eq",
# stringsAsFactors = FALSE)
# saveRDS(shapeData,file="data/yahara_shapefile_data.rd... |
3ce8532047b80125c3a0f1c636dc105ccbf75a33 | 9e72f2d88e396432a7bdf217c8408f8a1fff02e8 | /wordcloud2_project.R | 969c76667074b4db3090c49ec204a2c35cfacf6e | [] | no_license | SeokHyeon-Hwang/R_data_analysis | 271cdc33b601d0cc61788e4a0fc1e51795daccbd | 61c4af51e1cac736a0290c6ac6c2dc2a927256f1 | refs/heads/master | 2021-07-11T23:02:26.650102 | 2019-03-05T04:52:33 | 2019-03-05T04:52:33 | 148,569,523 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,555 | r | wordcloud2_project.R | rm(list=ls())
# clawling & wordcloud2
## 01.clawling
# install.packages('rvest')
library(rvest)
### data road from wed(movie review)
all_reviews<-c()
test<-paste0('https://movie.daum.net/moviedb/grade?movieId=109924&type=netizen&page=', 2)
test
### read html
htxt=read_html(test)
htxt
table=html_nodes(... |
a6af73dfe2941a352d7b8c7128ba30fdf95026c6 | 77157987168fc6a0827df2ecdd55104813be77b1 | /onlineforecast/R/operator_multiply.R | 2ce598f0d54a20521110444b2659c834264555a9 | [] | no_license | akhikolla/updatedatatype-list2 | e8758b374f9a18fd3ef07664f1150e14a2e4c3d8 | a3a519440e02d89640c75207c73c1456cf86487d | refs/heads/master | 2023-03-21T13:17:13.762823 | 2021-03-20T15:46:49 | 2021-03-20T15:46:49 | 349,766,184 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,464 | r | operator_multiply.R | ## Do this in a separate file to see the generated help:
#library(devtools)
#document()
#load_all(as.package("../../onlineforecast"))
#?"%**%"
#' Multiplication of each element in a list (x) with y
#'
#' Each element of x is multiplied with y using the usual elementwise '*' operator.
#'
#' Typical use is when a functi... |
3df9fdf1351c52b17ac96dacbf29b2a6967278ef | 42cf1ccab678eb9a3b7df1e8b79b8addea0341ee | /man/recent_changes.Rd | cec02abbb19c8bee15ca7dae51182495a157f63a | [
"MIT"
] | permissive | cran/WikipediR | 936188140398c1ece227d72ea35d92e8c7da7e4c | 36e90097daf8623df2fcce9819b548d6f8824846 | refs/heads/master | 2020-12-29T02:38:25.834033 | 2017-02-05T07:44:55 | 2017-02-05T07:44:55 | 18,895,732 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 3,037 | rd | recent_changes.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/recent_changes.R
\name{recent_changes}
\alias{recent_changes}
\title{Retrieves entries from the RecentChanges feed}
\usage{
recent_changes(language = NULL, project = NULL, domain = NULL,
properties = c("user", "userid", "comment", "parsedco... |
21ad55cfbfb33001ca92b5cea24045df5602673e | 45e79381152047a7777d50271e38c726013be682 | /man/getExperimentContainers.Rd | 97f78151bd7122f82c2ab2e3bcc48f047e07df41 | [] | no_license | ceparman/Core5.3 | e13530d3fd7a457ee39935400766badddc5120bd | de8f6e946ca159332979807eba997b5efbf123d4 | refs/heads/master | 2020-03-23T08:08:06.929458 | 2019-02-06T14:24:36 | 2019-02-06T14:24:36 | 141,309,256 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,257 | rd | getExperimentContainers.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getExperimentContainers.R
\name{getExperimentContainers}
\alias{getExperimentContainers}
\title{getExperimentContainers - Gets experiment containers from experiment identified by barcode.}
\usage{
getExperimentContainers(coreApi, experimentTy... |
3e2a2697610d828ff4873c7e07a74d2b33074557 | bf380c13cfeb3fa08ee3d54d79f2fbaac0cc50b9 | /Week1/UsingR.R | 39ac92a56b146e82c8e02dcdfe3ce1918dd9c08e | [] | no_license | vitorpbarbosa7/RegressionModels | 7b2d4a82091543d5221b35752df0ee14dc87ed6b | 70158d2a62cff63e14a096de0c0df976cd972f7f | refs/heads/master | 2023-03-11T04:32:32.713550 | 2021-02-26T16:47:24 | 2021-02-26T16:47:24 | 288,875,558 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 317 | r | UsingR.R | library(UsingR)
# Carregar os dados -------------------------------------------------------
#Dados utilizados por Galton em 1885
data("galton")
library(reshape)
long = melt(galton)
g = ggplot(long, aes(x = value, fill = variable)) +
geom_histogram(colour = "black", binwidth = 1) +
facet_grid(.~variable)
|
f9f09aa9baf974963d00c00548e7567a2e2537b2 | 8a2b0cab64ac5f28bedfb06684774b2464bfa87c | /functions/PAF.R | 861e87058a111d382a20e272b15b7d3eea96d98b | [] | no_license | walkabillylab/ITHIM-R | 037264528ffef905a8c9b32c4f9500d8601bae63 | d6809907950af715a68d03c4a4dcd6851170994e | refs/heads/master | 2020-04-02T06:13:15.504959 | 2018-11-06T15:55:35 | 2018-11-06T15:55:35 | 154,136,680 | 0 | 0 | null | 2018-11-06T15:55:37 | 2018-10-22T12:06:04 | HTML | UTF-8 | R | false | false | 173 | r | PAF.R | PAF <- function(pop, cn, mat){
##!! hard coding of indices: 1=sex, 2=age or age_cat
paf <- apply(mat,1,function(x)sum(pop[[cn]][pop[[1]]==x[1]&pop[[2]]==x[2]]))
paf
}
|
be363b0b6002d7b8dcd9fdf38584f6cc7c8edeec | 3dad5087fae24d0dd09803e7dd0e8511f96dac76 | /man/do_the_perms.Rd | b8fe16f4f7e386ac11790adb456d9366c4c82cf3 | [
"LicenseRef-scancode-public-domain"
] | permissive | eriqande/inbredPermute | badecc3a6b955d8f5aa1842b44b6a588d53e6991 | dfc9ff6085199187f8b21c8cc3050b3f7999800d | refs/heads/master | 2020-03-30T02:55:29.136330 | 2014-10-22T19:04:15 | 2014-10-22T19:04:15 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 275 | rd | do_the_perms.Rd | % Generated by roxygen2 (4.0.1): do not edit by hand
\name{do_the_perms}
\alias{do_the_perms}
\title{function to do the permutations}
\usage{
do_the_perms(kg_file, trio_file, meta_file, REPS = 1000,
ItalianCommas = FALSE)
}
\description{
function to do the permutations
}
|
16703ab9668ed1105c86f02e83c4ea5427e3bbb8 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/seewave/examples/simspec.Rd.R | 369eddddc54717e3500a750732a3bd46d1ba307e | [] | 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 | 987 | r | simspec.Rd.R | library(seewave)
### Name: simspec
### Title: Similarity between two frequency spectra
### Aliases: simspec
### Keywords: dplot ts
### ** Examples
a<-noisew(f=8000,d=1)
b<-synth(f=8000,d=1,cf=2000)
c<-synth(f=8000,d=1,cf=1000)
d<-noisew(f=8000,d=1)
speca<-spec(a,f=8000,at=0.5,plot=FALSE)
specb<-spec(b,f=8000,at=0.5... |
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