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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
cc742b32ba479cef166565fc0f59d447c57d3ada | 396df2552224ffcb0294fe6e297b231aa2e59e68 | /_working/0129b-fuel-prices.R | 8a7e24104ac271533f61dd360ed0f89ea8c24439 | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | ellisp/blog-source | d072bed980a5074d6c7fac03be3635f70ab5f098 | 1227f83df23af06da5280214ac7f2e0182be5707 | refs/heads/master | 2023-09-05T07:04:53.114901 | 2023-08-27T21:27:55 | 2023-08-27T21:27:55 | 122,695,494 | 17 | 8 | null | 2023-08-27T21:15:33 | 2018-02-24T02:36:45 | HTML | UTF-8 | R | false | false | 4,106 | r | 0129b-fuel-prices.R | library(tidyverse)
library(scales)
library(openxlsx)
library(forecast)
library(nlme)
# download manually from https://www.dropbox.com/s/i75ha9n1jc0vm2c/fuel%20prices.xlsx?dl=0
# edit the "Central Plateau" sheet by setting the whole "Date" column to be in date format
fn <- "fuel prices data 2.xlsx"
sn <- getSheetNames... |
dd028762e5d2588a23ef48def96fef93fdef4322 | 0f8a97baf9c9373ea62476abbce05bf8f89a9363 | /furnaceCycle.R | ebc916fa1ab0aad2e8a84d87ae3a6bc2f4f5201f | [] | no_license | tastyCanOfMalk/historical.MAL | 642d5b3fcef9a020f48d92d0593f6a72cf9dceaf | 7f34f2496e4ef70182415a85df1a7c614f73d268 | refs/heads/master | 2020-04-20T09:35:06.681740 | 2019-07-24T13:59:06 | 2019-07-24T13:59:06 | 168,768,666 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,454 | r | furnaceCycle.R |
# since aluminum uses a different furnace, change all to NA
x$furnace.cycle[x$alloy=="aluminum"] <- NA
# test df
# select first letter to call furnace
xx <- x %>%
select(request, furnace.cycle, alloy) %>%
filter(alloy != "aluminum") %>%
mutate(furnace = str_sub(furnace.cycle,1,1)) %>%
mutate(cycle = NA) %... |
533036a9d615ac81085b0287b86ca4c79143b9cc | 8f501777660f04ddadf06400074bc6b412c90fb9 | /IsoriX/R/create_aliens.R | 29c3b59d4ad3de9ce9746da0a69132a30b18c8e6 | [] | no_license | PhDMeiwp/IsoriX_project | db0e323fd2822a98cf16c4708fc9ef31df85b9f8 | 14510f948a3497a99554e80d563a9131d40550c0 | refs/heads/master | 2020-03-09T18:24:08.128374 | 2017-08-14T08:23:56 | 2017-08-14T08:23:56 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,439 | r | create_aliens.R | #' Simulate datasets for calibrations or assignments
#'
#' This function allows to simulate data so to provide examples for the
#' calibration and for the assignment procedure. We name the simulated
#' individuals 'Aliens' so to make it clear that the data we use to illustrate
#' our package are not real data.
#'
#'... |
31b2be8bac49fe470ff7ac43b941c1a2e63db36c | 4700c8fa4b68ee1b2e02be10bbab72d60daed6c5 | /R/beta.ab.R | aaa8ea31ead615ef4990751ef61cb917024b6aba | [] | no_license | alyssamv/iAdapt | 95e1b1826ccd40c64a7701b08c329e05d0bbe531 | 65c3912d66e77ee4172aadb9ebdc3205a85408fd | refs/heads/master | 2021-08-07T12:15:23.490531 | 2019-08-28T15:07:33 | 2019-08-28T15:07:33 | 155,378,228 | 1 | 0 | null | 2019-08-13T22:52:33 | 2018-10-30T12:02:32 | R | UTF-8 | R | false | false | 1,155 | r | beta.ab.R | #' @title Generates parameters for the beta distribution # I don't think we need to show this as a separate function,
#' but put together with gen.eff.stg1 or be called by gen.eff.stg1
#'
#' @description Function \code{beta.ab()} returns parameters alpha and bet... |
c34ec91b0e8af7fd5bfe9c2187775e472008e891 | cea3466a2947e429a4f4fff5a65df740241c8190 | /R/pdims.R | 4df3830cfd54da8a57a8dcbd5b89fcfe73468a68 | [
"MIT"
] | permissive | cran/term | 73420e2257b6a0ed12a063a0133ec1e25ba4aa3d | 167b06989f44e37d0dd592b0a7ff5470edd91b65 | refs/heads/master | 2022-10-08T15:13:04.078807 | 2022-09-29T15:20:11 | 2022-09-29T15:20:11 | 236,950,026 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 908 | r | pdims.R | #' @export
universals::pdims
#' @details Errors if the parameter dimensions are invalid or inconsistent.
#'
#' A named list of the dimensions of each parameter can be converted
#' into the equivalent [term-vector()] using [term()].
#'
#' @inherit universals::pdims
#' @export
#'
#' @examples
#' pdims(term("alpha[1]", "... |
4c444b331e62b884eab2ee851fe51319cc66469c | c723b14038ea8628ceb74ce04e291c281cc976d4 | /R/ltx_sideways.R | dde8212a496d1627c40706f66b0e52c9d054405a | [
"MIT"
] | permissive | hokerl/ltxtab | a14b12dc3951789aa4e7f6a6fddb28267f56a1c0 | 483d2678d533b78f8620f347859572ea257e9717 | refs/heads/master | 2021-10-19T08:29:44.423944 | 2019-02-19T14:48:27 | 2019-02-19T14:48:27 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 370 | r | ltx_sideways.R | #' Rotate LaTeX cell contents
#'
#' @param df table data
#' @param row row number
#' @param col column number
#'
#' @return table data
#' @export
#'
#' @examples \dontrun{
#' ltx.sideways(df, "test", 1)
#' }
ltx_sideways <- function(df, row, col){
df <- as.data.frame(df)
df[row, col] <- paste0("\\begin{sideways}",... |
561508c4fd7cd93ab3758020f8ce937af39d5be8 | 06d57535f6d974c4923a0882e967c2fd829f058e | /ClassPerformance/server.R | 75762126da0cd753fef6b7e8a8a977c0b6d60ea9 | [
"MIT"
] | permissive | dhadka/investr | 01cd1e1e0a659df627f1fc516dad16db6df0e9fd | a1705768196aaa8b0ced1d43b2c4d6895acf6eca | refs/heads/master | 2016-09-10T18:58:29.947885 | 2014-12-12T17:46:57 | 2014-12-12T17:46:57 | 23,683,643 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 8,082 | r | server.R | # Copyright (c) 2014 David Hadka
#
# 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, distri... |
210ec52c51ecc2f89cbd8f35e2f236c3672ba53d | b2a1bbadcfdec95b35702a96bb5817578bc64093 | /CaretProjectVisSVM.R | 2a66a38b673b8cba95c9c3aea8c23205aa5018a5 | [] | no_license | tenfoldpaper/caret_project | 35c2d01d5f0ec7c329d88b335368c0f052ef9db6 | 96e99383cc5cebdd8eef83f73a60fd483a3a86f1 | refs/heads/master | 2020-03-06T19:00:04.889269 | 2018-03-30T16:45:52 | 2018-03-30T16:45:52 | 127,018,560 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,896 | r | CaretProjectVisSVM.R | #SVM Visualisaion written by Seongjin Bien, TquanT 2018
library(shiny)
library(ggplot2)
ui <- fluidPage(
titlePanel("Graphs"),
sidebarLayout(
sidebarPanel(
radioButtons("vsize", "Select the training sample size:",
c("80/20" = "eightyTwenty",
"64/33" = "oneThird"... |
2b2af28122276fb3211cb48967d28cfdcff79083 | 608ec1c8c815281933c66861fca044b294e310d2 | /packages.R | 35973e9a5437567969ac93c2890e439d906101fe | [] | no_license | nohturfft/BDiB_2021_ChIP_Seq | 18ea7c3fac7aa4961550e83865a98477d6150796 | 758b3e29b0222e104abf57f1c4a85b724f2fcaa2 | refs/heads/main | 2023-03-23T12:22:26.621345 | 2021-03-11T17:15:46 | 2021-03-11T17:15:46 | 346,429,977 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,544 | r | packages.R | #################
# Load packages #
#################
# Help for specific packages can be obtained as shown in the code chunk below
# (remove the '#' to run the code).
# help(package="ChIPpeakAnno")
# help(package="biomaRt")
library(readr)
requireNamespace("knitr")
library(scales)
# **LChIPpeakAnno package (https:... |
06d2e50c0c7eb9112a0fdb569a62d160c76f0bfe | 2c116d1ab776aa297d80e864fb4c7b9b9e44f62d | /r-package-setup.R | 83ffe57723f6c7cdf0e2a860288bef44d09cf7ea | [] | no_license | jaybee84/r-packages | b07a9e9d4273ef2b7fbb1dfb82046749ee553406 | d1cd077323c7540478c3c2f05c1a5d6bb037cfc8 | refs/heads/master | 2020-08-28T05:46:08.928340 | 2019-10-25T18:45:49 | 2019-10-25T18:45:49 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 748 | r | r-package-setup.R | ###############################
#### Set up an R package ####
###############################
library("usethis")
library("devtools")
## Create package structure
create_package("mypackage")
## Helper functions to customize package, e.g.:
use_mit_license("My Name")
## Check package with devtools
check()
## Add a n... |
2d3474129a85b9c51bd591474b480c9b4a4c4270 | d1ed29eb17fd79cd5adfa4276254c973f3d3c60a | /man/dpr_create_package.Rd | 3eadc8775fce3742ca49718ee125ecd95dfa813d | [
"MIT"
] | permissive | BYUIDSS/DataPushR | f7527a6ab34a1de08e2e71b508a89bb21b519073 | 561365687a35b030ea57303ecf9a99d8f8d3af22 | refs/heads/master | 2021-02-06T00:26:01.292411 | 2020-05-29T19:51:35 | 2020-05-29T19:51:35 | 243,853,077 | 2 | 2 | null | null | null | null | UTF-8 | R | false | true | 984 | rd | dpr_create_package.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dpr_create_package.R
\name{dpr_create_package}
\alias{dpr_create_package}
\title{Create an R package for data}
\usage{
dpr_create_package(
package_name,
export_folder = getwd(),
git_remote,
list_data = NULL
)
}
\arguments{
\item{packa... |
144486447fd65249f9940ecd65926105fde65048 | b05693137745a6706707b786d94fa01124864ca8 | /man/safely.Rd | db075ca685773922466da65c9c35cd542baddae4 | [
"MIT"
] | permissive | BB1464/purrr | f19ea507aacba57ae636eab26192498bd094183c | 5aca9df41452f272fcef792dbc6d584be8be7167 | refs/heads/master | 2023-05-09T07:58:33.385849 | 2021-04-12T07:24:19 | 2021-04-12T07:24:19 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 3,329 | rd | safely.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/output.R
\name{safely}
\alias{safely}
\alias{quietly}
\alias{possibly}
\alias{auto_browse}
\title{Capture side effects.}
\usage{
safely(.f, otherwise = NULL, quiet = TRUE)
quietly(.f)
possibly(.f, otherwise, quiet = TRUE)
auto_browse(.f)
}... |
1d45f084b5735b79cd48f775981ebf6cb893c5ef | 2af16e2c4eb8f17acd739349d3b7f8eab00124d1 | /R/mainKmeans.R | 414a034054f55703b636e56df4a0511ea3dc7f44 | [] | no_license | boulbi777/k-means-clustering-using-cpp | 6e954daa3dd096ae82cb4fab32099a809740930d | 8613b45c25c4794be0b6048740f01d2b9c47f9cb | refs/heads/master | 2022-12-12T22:13:10.754701 | 2020-09-06T13:37:36 | 2020-09-06T13:37:36 | 293,289,606 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,601 | r | mainKmeans.R |
###################################################################################
##' Cette fonction effectue la somme entre deux nombres
##'
##' @param x numeric. Matrice des donnees (1 ligne par observation).
##' @param K numeric. Nombre de clusters.
##' @param nbinit numeric. Nombre d'initalisations aléatoires de... |
e6507f23e98c4c2c3e9970a0a5f688bf50f55764 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/PMCMR/examples/posthoc.friedman.nemenyi.test.Rd.R | 8de72c1986c750f9d142639ea368a3712d169ff1 | [] | 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 | 956 | r | posthoc.friedman.nemenyi.test.Rd.R | library(PMCMR)
### Name: posthoc.friedman.nemenyi.test
### Title: Pairwise post-hoc Test for Multiple Comparisons of Mean Rank
### Sums for Unreplicated Blocked Data (Nemenyi-Test)
### Aliases: posthoc.friedman.nemenyi.test
### posthoc.friedman.nemenyi.test.default
### posthoc.friedman.nemenyi.test.formula
### ... |
72ae9e1b17f36df204d7e16f3d4bfa34999f5c5a | 7081286a0f4ae00c3cbf4e52a1fa96ec461a02c1 | /medical-data/SLNB/GPT-kaplan-meier3.R | d3378c917d1c70d438f6d80e3e27414715fd2b66 | [
"Apache-2.0"
] | permissive | kapsitis/ddgatve-stat | 98aea8d020f2f8e7ba66559cb59dc6367f2cce60 | 86b867bb16a11da3619be149f60e4dfd6474e0bb | refs/heads/master | 2023-05-04T02:45:53.879448 | 2023-04-23T13:26:08 | 2023-04-23T13:26:08 | 18,703,292 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,846 | r | GPT-kaplan-meier3.R | # (1) -demorāfisko eglīti
# (2) -stabiņi cik slnb taisīja un cik netaisīja
# (3) -pa vecumiem slnb veica slnb neveica
# (4) -stadijas(IA,IB, IIA ,IIB, IIC) slnb veica slnb neveica
# (5) -lokalizācijas slnb veica slnb neveica
# (6) -lokalizācijas male/female
# ***(7) -Kaplana-Meijera ar izčūlojumu un bez izčūlojuma (un ... |
8c3bf7a72901c7e3469b270437a422a783a1e938 | 40234ef2ad5efa4c566ff501f3972ab03b181bd9 | /code/figures/Fig6_hovmoller_mgmt_decisions.R | 06134efb87c8dc654bf00033eaba2bc192d4995d | [] | no_license | cfree14/domoic_acid | 63fefd3c577d0cd277747254aa50f425401c438f | dfe6f4d9b94ad7a71c092c92bf63100a46cb3d0c | refs/heads/master | 2023-07-15T10:28:49.815164 | 2021-08-25T22:31:47 | 2021-08-25T22:31:47 | 279,933,613 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 14,946 | r | Fig6_hovmoller_mgmt_decisions.R |
# Clear workspace
rm(list = ls())
# Setup
################################################################################
# Packages
library(sf)
library(raster)
library(tidyverse)
library(lubridate)
library(grid)
library(gridExtra)
# Directories
inputdir <- "input"
preddir <- "output/model_preds"
hovmollerdir <- "... |
322e5aa9faa202ec6d020dff9cd3582addde5776 | cfacbfb653f0662be0c70d2c6659c3d1d3305b71 | /Computational-Statistics/HW3.R | c78fd2888e27b321fe2f15a6c68b1e3f811e41f8 | [] | no_license | ihaawesome/Graduate | 37327af1acd4b2f2bf56648485e5a8378a2bbddd | a0ee4b8863b2cd03855685d17cab802e2b5898d3 | refs/heads/master | 2020-05-03T07:46:48.563738 | 2019-09-17T05:49:38 | 2019-09-17T05:49:38 | 178,507,439 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 5,774 | r | HW3.R | library(dplyr)
library(ggplot2)
library(GenSA)
library(GA)
# (1) kmeans
set.seed(1234)
x1 = matrix(rnorm(100, sd = 0.5), ncol = 2)
x2 = matrix(rnorm(100, 1, sd = 0.5), ncol = 2)
x = rbind(x1, x2) ; colnames(x) = c("x1", "x2") ; x = as.data.frame(x)
kmean = kmeans(x, 2, nstart = 10) ; kmean
ggplot() + th... |
e18a294a9b4cd6d70da9b6fd28c11a9920a9d4e0 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/Scalelink/examples/FOI.Rd.R | eec859f2d12afe9c2d0f1d29961a8e2002a8e08e | [] | 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 | 170 | r | FOI.Rd.R | library(Scalelink)
### Name: FOI
### Title: File of interest
### Aliases: FOI
### Keywords: datasets
### ** Examples
data(FOI, package = "Scalelink")
summary(FOI)
|
f78745df4cbf7f28f9a8d4ba2fddd3775c2ec189 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/openintro/examples/toohey.Rd.R | 4f4001b70b3aa49e1a30ea9af782f28a7ff2aa20 | [] | 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 | 193 | r | toohey.Rd.R | library(openintro)
### Name: toohey
### Title: Simulated polling data set
### Aliases: toohey
### Keywords: datasets
### ** Examples
data(toohey)
## maybe str(toohey) ; plot(toohey) ...
|
8a7a1ba2b8977b19596d74f7f6c5eb3a1bdb150c | 26b0fcba9fde7cf9ccdb0423f768ca417a6ce4ec | /tests/testthat/test_assemble_bsplines.R | c7541a980a3de5303da8467745f00d3a6b2b5037 | [] | no_license | cran/hero | 5334a80aae95acdffa48003ded4e35922d862d21 | 6608b2b4953706ed19d447b554d0e288ef6e33f4 | refs/heads/master | 2023-07-26T05:45:27.750716 | 2023-07-15T21:10:09 | 2023-07-15T22:32:24 | 155,420,413 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 597 | r | test_assemble_bsplines.R | context("check assemble.hero_bsplines")
s = seq(0, 1, len = 101)
test_that("assemble.hero_splines matches pspline.setting", {
nk = seq(10, 25, len = 4)
o = 1:4
mc = 1:5
for (i in seq_along(nk)) {
for (j in seq_along(o)) {
for (k in seq_along(mc)) {
list1 = pspline.setting(s, knots... |
9c88d3f3cc131cf1cd83da3d5bced7e961b33646 | 807f70d6951c6cd928ea4b72cb3e644cf997678a | /man/get_project_walkthroughs.Rd | 1ff6db7e91428309dbcdc5a01de80477ed447ff6 | [] | no_license | jonlinca/galvanizer | c1574365374b10676c23e05c8b298ddf2ef30980 | b2e5a767b3a317bf18437515d8dca801668955d2 | refs/heads/master | 2023-05-06T20:20:05.016669 | 2021-05-28T16:19:36 | 2021-05-28T16:19:36 | 277,917,653 | 2 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,092 | rd | get_project_walkthroughs.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/projects.R
\name{get_project_walkthroughs}
\alias{get_project_walkthroughs}
\title{Retrieve Highbond Project - Walkthroughs / Execute Procedures}
\usage{
get_project_walkthroughs(
auth,
walkthrough_id,
fields = NULL,
pagesize = 50,
... |
9958ef9b5ec0f412d162bde492d51ce1179536a1 | 3ced8c2cb355a188ec610e7f288b2cdda2bbfcc1 | /materyaller/kodlar/ggplot2_baslangic.r | 01de79ba140ca00415177af3d2715a3e0acc2d7e | [
"MIT"
] | permissive | r338/ab-2016 | b99bf1817f340f9821260d78532f02c5ae79d807 | 9625abf936cd35a3d90f3c4602921f13241f765c | refs/heads/master | 2021-01-10T04:52:15.747960 | 2016-02-02T12:31:34 | 2016-02-02T12:31:34 | 50,600,817 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,852 | r | ggplot2_baslangic.r | ##ggplot2 ornekleri
options(stringsAsFactors=FALSE) #data.frame yapısında characterleri factor değil character şeklinde tanımla
options(dplyr.width = Inf) #dplyr tablolarının genişliğini tam göster
options(scipen = 7) #Ondalık verilerde bu derinliği kullan
# install.packages("dplyr")
# install.packages("ggplot2")
li... |
f2f0446d220d47d065948384828230d6c1c5ffaa | e760ec7eff2aa44cd87e85a6fcb18b9e82240f44 | /man/format_exp_data.Rd | 2ea2d55885fdb1b0c4ea1f3d5248843f3c0bdb73 | [
"MIT"
] | permissive | fentouxungui/CryptDriftR | 81ec9372c5553aae3fb20e37077fd62f24039372 | ee708eeecfd47d9e6ea43ddcf59394f4a7f207da | refs/heads/master | 2023-06-30T13:05:19.418613 | 2021-08-05T16:16:31 | 2021-08-05T16:16:31 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 666 | rd | format_exp_data.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/format_data.R
\name{format_exp_data}
\alias{format_exp_data}
\title{Calculate proportions with 95\% credible interval (confidence interval).
If there are replicates they will be pooled(!). It will work for both count table format and list for... |
014f7f4d8b2b96e838a3abaf5470415abc83faea | 401f2375173bd502cb7419230bc4c75c530c9b6e | /man/monetdb.read.csv.Rd | 09340ea86c4280f6a64672dedf1005d7446b3fef | [] | no_license | MonetDB/MonetDBLite-R | cab5c16538ed215eaf5d3aa36085e6d7b0f6dfb6 | 3fa31575efd66c673b67c9ddb24e5668a397a047 | refs/heads/master | 2023-08-28T00:40:36.593695 | 2022-01-13T09:02:00 | 2022-01-13T09:02:00 | 103,245,827 | 19 | 8 | null | 2019-09-20T08:05:01 | 2017-09-12T08:49:13 | C | UTF-8 | R | false | false | 2,390 | rd | monetdb.read.csv.Rd | \name{monetdb.read.csv}
\alias{monetdb.read.csv}
\alias{monet.read.csv}
\title{
Import a CSV file into MonetDBLite
}
\description{
Instruct MonetDBLite to read a CSV file, optionally also create the table for it.
}
\usage{
monetdb.read.csv (conn, files, tablename, header=TRUE,
locked=FALSE, best.effort=FALSE... |
12d066350579c9f3b5e866df8061ac0090ecc551 | 63a770312db431190f9bf7db60dacdb86134fa76 | /src_raw/2.5_KEGG_DEG.R | 253b5a43a7df115433d8cc8e983942a492c11371 | [] | no_license | zhilongjia/nCoV2019 | 0ee4aab7dcc35a4273a36dd4be97e9b6d85c55f3 | 57b616e83aa638fbfcdd4be09101e0c4331eb0e0 | refs/heads/master | 2023-02-20T11:17:52.551457 | 2020-07-25T08:00:21 | 2020-07-25T08:00:21 | 236,764,272 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,102 | r | 2.5_KEGG_DEG.R |
load("../results/DEA_list.RData")
load("../results/DEA_pneu_list.RData")
symbol2entrezID <- function(gene_symbols) {
symbol_ENTREZID <- clusterProfiler::bitr(gene_symbols, fromType="SYMBOL", toType="ENTREZID", OrgDb="org.Hs.eg.db")
return(symbol_ENTREZID$ENTREZID)
}
DEA_list <- c(DEA_list[["limma_DEG"]], DE... |
047ad96c7e2682f7efb9893a4614065deb95b5ad | 1d023a92fe9b31ebfd21a845ba4e928dad2e848a | /binomial/tests/testthat/test-auxiliary.R | 5516649df3040ff6b26e2f18241557a9cfc3fbaa | [] | no_license | stat133-sp19/hw-stat133-jsbshin | 4051317b9de69a4329dd10fdc7ada093479069ea | 9d2e9a9d116f9f0f6fa7f989ba627703a76cc56d | refs/heads/master | 2020-04-28T10:30:31.881685 | 2019-05-03T18:01:52 | 2019-05-03T18:01:52 | 175,203,557 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,462 | r | test-auxiliary.R |
context("test auxiliary functions")
# test aux_mean() function
test_that("test that aux_mean works",{
expect_equal(aux_mean(10, 0.5), 5)
expect_equal(aux_mean(100, 0.3), 30)
expect_equal(aux_mean(1000, 0.1), 100)
expect_error(aux_mean('a', 0.3))
expect_length(aux_mean(10,0.5),1)
expect_is(aux_mean(10,0.5)... |
61ba1d34596e13f87f30a92972d87e68bdfcd1f3 | f499f99b54008f18e3aa128ff41e94748deb5626 | /man/mlr_learners_ordinal.clm.Rd | 86e272a42ad29506d53dd7c0bcb98a2223845626 | [
"MIT"
] | permissive | mlr-org/mlr3ordinal | 93bb02bc10689a45ba3001c49ee892cf5dc18b32 | 026d8507baaac4e9bc44eb8c074b5b0363305122 | refs/heads/main | 2022-12-22T02:22:18.115673 | 2022-12-08T13:33:05 | 2022-12-08T13:33:05 | 164,665,475 | 4 | 0 | MIT | 2022-12-08T13:32:31 | 2019-01-08T14:24:31 | R | UTF-8 | R | false | true | 410 | rd | mlr_learners_ordinal.clm.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/LearnerOrdinalClm.R
\name{mlr_learners_ordinal.clm}
\alias{mlr_learners_ordinal.clm}
\alias{LearnerOrdinalClm}
\title{Cumulative Link Model Learner}
\format{
\link[R6:R6Class]{R6::R6Class} inheriting from \link{LearnerOrdinal}.
}
\description... |
c2c6a4f0789ac89178b8e5a1a3aa621ef2ade003 | c5339895b90adeb68db2317f82057a8a70ee763a | /paper_examples/results/muscle/dend.R | ccf760ab3ea0411e872374279d2318e3ec784746 | [
"MIT"
] | permissive | PengTao-HUST/GDNB | 966ccfd06e5fa59dca0923cb0bd59f9cc9c8743e | e38ad0e316a2ff4c68bed06217e685d55452a49c | refs/heads/master | 2023-07-28T05:59:45.572835 | 2021-09-09T16:36:30 | 2021-09-09T16:36:30 | 402,607,387 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,831 | r | dend.R | install.packages('pheatmap')
library(pheatmap)
install.packages("factoextra")
library(factoextra)
data = read.table('../../figures/muscle/expr.txt')
df = as.matrix(data)
#df[which(df < 5, arr.ind = T)] = 5
#df[which(df > 15, arr.ind = T)] = 15
dfs = apply(df, 1, scale)
dfs = t(dfs)
dfs[which(dfs < -2, arr.ind = T)] ... |
6623d55f77a9ad5192a6fb534f110b4fa992bac3 | b8a19cc9c443d367da8ce10c435a8c7d9bbffa9b | /man/plot.missingness.Rd | e263e2fcac9aaecf8858f1a2c655b1f3b41c7a9c | [
"MIT"
] | permissive | g3rley/healthcareai-r | 9b0a68cc5406f2af2a85dc5318769a94075787a6 | 9b00c1be1daaa5c387ecee910d7571684447e4ff | refs/heads/main | 2023-07-21T19:08:15.174485 | 2022-09-01T17:16:55 | 2022-09-01T17:16:55 | 451,652,775 | 1 | 0 | NOASSERTION | 2022-01-24T22:20:57 | 2022-01-24T22:20:57 | null | UTF-8 | R | false | true | 1,110 | rd | plot.missingness.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/missingness.R
\name{plot.missingness}
\alias{plot.missingness}
\title{Plot missingness}
\usage{
\method{plot}{missingness}(
x,
remove_zeros = FALSE,
max_char = 40,
title = NULL,
font_size = 11,
point_size = 3,
print = TRUE,
..... |
744ff39998fde4b8c62f574205417d1588e6c5eb | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/tor/tests/test-list_any.R | d57a29d0ccf6db3f65a702ed7aec42b3acfcea22 | [] | 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 | 2,304 | r | test-list_any.R | context("list_any")
test_that("list_any with read.csv lists (file)named dataframes", {
res <- list_any(
tor_example("csv"),
utils::read.csv,
regexp = "[.]csv$"
)
expect_is(res, "list")
expect_named(res, c("csv1", "csv2"))
expect_is(res[[1]], "data.frame")
expect_is(res[[1]], "tbl")... |
b012c9edcc1e66c8cd6833ec6b5f88a5c856f4c4 | 1460dc122a0cb6584ed382135f78e78d2520030a | /test.R | 56436210ec762560f744470200ff4ab3f1f6cdc7 | [] | no_license | douglasquinn/programmingPrepClass | ec626835ba9ce3a4f9055a1f03c9bd7854613e73 | b5c71a1dcc9e8b37e58de1cf5dd71ecb42058f69 | refs/heads/main | 2023-08-04T09:58:52.990083 | 2021-09-30T23:07:15 | 2021-09-30T23:07:15 | 410,948,898 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 35 | r | test.R | stats <- load("stats.rdata")
stats
|
50542ed24ab03e857fa761bf0a8b3c3cb405269b | 68eaf6ab25ad2af91fbcffd994b1f0dbe710b801 | /Unif_one_samp.r | 966f291e38124d10317fe2072da3a5b311aaa266 | [] | no_license | idc9/FalseConfidence | ac13107f8d9bb6df2d93bfe19d3e6027738113a1 | 6b8a1c0d55a21a1cf97c579f02cf9ae3dbbf50fe | refs/heads/master | 2020-03-23T02:39:19.631187 | 2018-07-19T02:14:50 | 2018-07-19T02:14:50 | 140,984,669 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,474 | r | Unif_one_samp.r | library(latex2exp)
set.seed(1000)
# Sampling probability of the event P(A^c) < alpha.
pFun = function( epsilon, alpha, n, theta_0){
s11 = (theta_0/(theta_0-epsilon))^n - (theta_0/(theta_0+epsilon))^n
s1 = min( 1/alpha, s11^(-1)) * ((theta_0-epsilon)/theta_0)^n
s2 = ((theta_0+epsilon)/theta_0)^n
s3 = (epsilon <... |
ec58ace58e2831b4bf407ae8a56bb20f8ccd2aac | 96dac3b379db632cc577600f1041ecafbddca400 | /Working scripts/The final scripts (sourced scripts)/distribpart.R | b240f03293dcfb8c817d6dc4c9b6db3fab81c566 | [] | no_license | kaye11/Some-R-scripts | 78e53b0c37254945120fca91255801b392835cb1 | 632b16a3269c7ce5c7c14efceb26fb02bf66eac1 | refs/heads/master | 2021-01-23T06:44:20.200098 | 2016-09-01T18:56:25 | 2016-09-01T18:56:25 | 21,462,015 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,977 | r | distribpart.R | library(ggplot2)
library(reshape)
##always use data from t1
library(data.table)
NT = data.table(t1)
NT2=NT[, T := seq(from = 1L, by = 1L, length.out = .N), by = A]
##for distrib particles analyis
NTS <- aggregate( A ~ T , data = NT2 , max, na.rm = TRUE )
#every min
qplot(T, A, data=NTS [NTS$T<61, ])+ labs(list(x = "... |
9f217a1e5ce77f447e58489cfdf5f432a1f7ed20 | 950fb55ee7441e4d0ddeeb858b4c47641675c5d2 | /regression/data/data_setup.R | 9b56e660e3d902fee4af95865245575f3ee53cd5 | [] | no_license | lmyint/shiny_education_apps | 5a658316862c2dff16f1b8e9173603fe7fead10a | d78384530eeeb26956e3d274d5c44142b22ad809 | refs/heads/master | 2021-01-16T18:26:31.725792 | 2017-10-10T17:59:54 | 2017-10-10T17:59:54 | 100,080,427 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,456 | r | data_setup.R | library(readr)
library(glmnet)
library(dplyr)
## Kaggle: Wisconsin breast cancer data
bc <- read_csv("breast-cancer-wisconsin-data.csv")
colnames(bc)[colnames(bc)=="concave points_mean"] <- "concave_points_mean"
colnames(bc)[colnames(bc)=="concave points_se"] <- "concave_points_se"
colnames(bc)[colnames(bc)=="concave ... |
022aefa7da2022c06a5664262f7e1fb98e24c723 | eb127bbb4e75966296b4a2234250ba6819e513b1 | /code_analysis_obj/utils.R | 7ddb68890c461f6d89b1318cd04be50647a61f53 | [] | no_license | davidchampredon/stiagent | 29cc33cc8e1a54763ccd5f12f05949ac80354575 | dc6cd187b7649ee4517fc27ea66aff377c8ff892 | refs/heads/master | 2021-01-10T12:50:45.273558 | 2016-03-21T03:45:58 | 2016-03-21T03:45:58 | 43,753,973 | 0 | 0 | null | 2015-11-18T01:53:12 | 2015-10-06T13:56:06 | C++ | UTF-8 | R | false | false | 2,413 | r | utils.R |
library(plyr)
library(dplyr)
library(tidyr)
get.nMC <- function(sim){
### RETURN THE NUBER OF MONTE CARLO ITERATIONS
return(sum(grepl("MC_",names(sim))))
}
get.timeseries <- function(sim){
### RETRIEVE ALL TIME SERIES (FOR EVERY MC ITER)
### IN A DATA FRAME FORMAT
stinames <- sim[[1]]$STInames
n.sti <- le... |
042809a2eceb0438d709474e659bc6581e5f5b90 | 63e1231faa30a4cea6dd9f25e87c2372383aa2f4 | /R/Data_documentation.R | 2e12472cbd055a48075559de841226d299378a58 | [] | no_license | cran/MSEtool | 35e4f802f1078412d5ebc2efc3149c46fc6d13a5 | 6b060d381adf2007becf5605bc295cca62f26770 | refs/heads/master | 2023-08-03T06:51:58.080968 | 2023-07-19T22:10:23 | 2023-07-20T01:47:18 | 145,912,213 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,215 | r | Data_documentation.R | # This file is automatically built by build_tools/build_data.r
# Don't edit by hand!
#
#' @rdname Stock-class-objects
"Albacore"
#' @rdname Stock-class-objects
"Blue_shark"
#' @rdname Stock-class-objects
"Bluefin_tuna"
#' @rdname Stock-class-objects
"Bluefin_tuna_WAtl"
#' @rdname Stock-class-... |
c117e8b2a3cf3e196ea6dd55f1e9a37625506eb0 | aa6c6c778f43c75d40a40c0599ebfc2a31f5267d | /01_clean-data.R | 54a26727da8b31097f03b43f844e9228ed466a9a | [] | no_license | wbeck1990/temp-nutrient-interactions | 5770720687244d97fd87e805d7f89297f2626c9f | 06d5225fe83ff64ba4dff703addee06bb6c836a1 | refs/heads/master | 2020-04-05T02:00:19.944409 | 2018-12-18T16:36:22 | 2018-12-18T16:36:22 | 156,459,861 | 0 | 0 | null | 2018-11-06T22:59:12 | 2018-11-06T22:59:12 | null | UTF-8 | R | false | false | 34 | r | 01_clean-data.R | # script to clean and wrangle data |
e04adff224966124239782418087647251138bdf | b20188200897e1b86950b186a143b18c38217ec8 | /bitcoinpred_old_algorithm.R | 8e15b1aae3fa861354044f083977916249cde745 | [] | no_license | roptanov/bitcoin | c751de61d7bca60221c98e11d6b6b8ec95a2b4db | cb4b33f0161912854a4bba1934206506288ca38d | refs/heads/master | 2021-08-23T12:01:45.093009 | 2017-12-04T20:40:08 | 2017-12-04T20:40:08 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,433 | r | bitcoinpred_old_algorithm.R | library(dplyr)
library(rusquant)
library(quantmod)
library(rpart)
library(rpart.plot)
library(caret)
library(curl)
library(nnet)
library(lubridate)
library(dplyr)
library("e1071")
library(ggplot2)
library(lubridate)
library(xts)
coindesk = read.csv('C:/Users/Ilya/Desktop/МОР/coindesk.csv', sep = ',', header=TRUE)
bitc... |
fcebd0b8c936324b2c9dfdf30ce66ce09a3d073c | 4b5c3f74e8ea6e6384fb4f3514e962b75af1b397 | /modules/analise/analiseUI.R | f89cd9ab44516f56584e2bcac42c41de02c46fab | [] | no_license | FelipheStival/inmetShiny | 3d4574ef99e4a4a875872d09abc144ccbe9c7a05 | bd9bb83a2ba90e69d96966928e260ba9ef872378 | refs/heads/main | 2023-05-14T23:37:14.285945 | 2021-06-06T23:25:19 | 2021-06-06T23:25:19 | 334,207,426 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,452 | r | analiseUI.R | #==================================================================
# Analise tabela UI
#==================================================================
analiseUI = function() {
tabItem(tabName = "tabelaAnalise",
tabBox(
width = "100%",
selected = "Tabela sumario",
tab... |
09578b7369aaf20884be16a6838f442b089ff5aa | 0a906cf8b1b7da2aea87de958e3662870df49727 | /diceR/inst/testfiles/indicator_matrix/libFuzzer_indicator_matrix/indicator_matrix_valgrind_files/1609959467-test.R | 9a0515496f6039581969ff1917eae0b1634e029f | [] | no_license | akhikolla/updated-only-Issues | a85c887f0e1aae8a8dc358717d55b21678d04660 | 7d74489dfc7ddfec3955ae7891f15e920cad2e0c | refs/heads/master | 2023-04-13T08:22:15.699449 | 2021-04-21T16:25:35 | 2021-04-21T16:25:35 | 360,232,775 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 181 | r | 1609959467-test.R | testlist <- list(x = c(1.01670330560775e-316, 7.39437241408225e-304, -8.53897486142116e-280, 2.1238739044437e-314))
result <- do.call(diceR:::indicator_matrix,testlist)
str(result) |
def4681c577aa1a6604154ee8ae60ede948a004c | e443c50f825638cace4d329e73fe6faeb9a9bad1 | /R/MagnesRutiner/vec.from.merds.to.farm.r | 589ad04f7e03ad65bc90640648ed8713755066fb | [] | no_license | Kotkot/RecaSimfish | 07b3d1773497d0887e1b4903b9449bbad46ca8a9 | 03c7a33a9a7d9419712f9b62953a4a67c4509552 | refs/heads/master | 2020-07-05T05:01:48.064166 | 2019-08-15T11:47:11 | 2019-08-15T11:47:11 | 202,530,801 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 558 | r | vec.from.merds.to.farm.r | vec.from.merds.to.farm<-function(x,antall.merds,antall.farm) {
n.merds<-length(x)
merd.names<-names(x)
tmp<-x[[1]]
dn<-dimnames(tmp)
time.names<-dn[[1]]
n.times<-length(time.names)
w<-antall.merds/as.vector(antall.farm)
w[is.na(w)]<-0
res<-vector("list",1)
names(res)<-"AllMerds"
### res[[1]]... |
66142e1ae074c3bfe986981b55ddec63f17f6ed4 | 77157987168fc6a0827df2ecdd55104813be77b1 | /CNull/inst/testfiles/communities_individual_based_sampling_beta/AFL_communities_individual_based_sampling_beta/communities_individual_based_sampling_beta_valgrind_files/1615829691-test.R | d760b08b9157073f9922e0d17e6d9326c17bca7f | [] | 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 | 431 | r | 1615829691-test.R | testlist <- list(m = NULL, repetitions = 0L, in_m = structure(c(2.43812608695272e-308, 2.08853788077799e-236, 2.05226840067026e-289, 3.33870925339418e-294, 1.44867561321978e+306, 1.41286214203445e-303, 1.44695764522227e-303, 1.18177156179874e-294, 1.45810387698431e-303, 1.38386568550094e-48, 0, 0, 0, 0, 0, 0, 0, 0)... |
53d8a015310c5c6e9c1b35742a86d04b678b8200 | c2dd13c7cc71651643d148b47dfacab970f39736 | /plot.R | 9bd442e300286190b08e7b364147949c85657456 | [] | no_license | shabss/exdata.proj2 | a0729c4f8d28acddf125c77c0e1ca60b890aa87d | babc594ea654592a8ea49a7aebadb1c95c7580ed | refs/heads/master | 2016-09-06T04:57:48.687139 | 2014-05-28T15:07:58 | 2014-05-28T15:07:58 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 140 | r | plot.R | source("plot1.R.txt")
source("plot2.R.txt")
source("plot3.R.txt")
source("plot4.R.txt")
source("plot5.R.txt")
source("plot6.R.txt")
|
94010a034f2cbc608c7d68dafd4eca651900fddf | 66a4d7725ab7f37d1d536bfcd284a8f6a64431b2 | /man/parse_status_response.Rd | 459175c0e30603e42dd69a18bab86f70170b4b59 | [] | no_license | meerapatelmd/glitter | 6ee867162657c2c83e80a02cf683bd132fde39d9 | 0b986b74682e2870b17c9bfc01112e2cbd42d046 | refs/heads/master | 2023-07-29T10:40:44.255146 | 2021-09-03T05:04:15 | 2021-09-03T05:04:15 | 296,978,497 | 1 | 0 | null | 2021-03-28T20:32:04 | 2020-09-20T01:09:41 | R | UTF-8 | R | false | true | 691 | rd | parse_status_response.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/print.R
\name{parse_status_response}
\alias{parse_status_response}
\title{Parse Response to Git Status}
\usage{
parse_status_response(status_response)
}
\value{
A list of vectors that has split on the following headers: "On branch","Changes t... |
9e8b3874a0e39fc30019b18a16e5d3b811b75ea8 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/sROC/examples/kROC.Rd.R | 2dd399c42c8e03f236e27e24300d87dce22c8c87 | [] | 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 | 300 | r | kROC.Rd.R | library(sROC)
### Name: kROC
### Title: Kernel Estimation for ROC Curves
### Aliases: kROC
### Keywords: nonparametric smooth
### ** Examples
## --------------------
set.seed(100)
n <- 200
x <- rgamma(n,2,1)
y <- rnorm(n)
xy.ROC <- kROC(x,y, bw.x="pi_sj",bw.y="pi_sj")
xy.ROC
plot(xy.ROC)
|
ed3047a37e2859d2b5c867a23021761a3de74bb3 | 00a6e8378c523b048399b3a7438f0fe22a6f5d4e | /R/engineer.R | 0b83bb433073836da1cbae78ea82593de6d44284 | [] | no_license | sxinger/DKD_PM_temporal | 46c117401ff7757ab440b216e4074efd5cf0bcb4 | dbbb35a2e18411422665958e27ecb1be7f675a62 | refs/heads/master | 2020-04-10T12:12:30.682542 | 2019-04-23T01:03:17 | 2019-04-23T01:03:17 | 161,014,841 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,403 | r | engineer.R | #### Feature Engineering ####
rm(list=ls()); gc()
setwd("~/proj_dkd/DKD_PM_wip")
source("./util.R")
require_libraries(c( "Matrix"
,"pROC"
,"dplyr"
,"tidyr"
,"magrittr"
))
fact_stack<-readRDS("./data2/DKD_heron_facts_prep.rda")
## a... |
b23d707a5f9d5f3a329543cf634dbe278f849c28 | 3bb6d71ba47f9d22185654565805fb69324020e3 | /TPM_Scripts/Making_Praveen-Mean_TPM_Dataset.R | a86c17ba371e28b8ad52624733763a0a7b2f6301 | [] | no_license | HongyuanWu/PanCan_RNA-Seq | c4b908f3ea80eebfd8c6358efc6fed36e06797ac | c1a82e41e1a1e6549ab853fc717f6b9e7fac2c9b | refs/heads/master | 2022-02-02T17:01:18.008193 | 2019-06-25T18:53:24 | 2019-06-25T18:53:24 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,261 | r | Making_Praveen-Mean_TPM_Dataset.R | rm(list = ls())
library(data.table)
library(dplyr)
library(magrittr)
library(stringr)
library(doParallel)
nCores <-
detectCores() %>%
subtract(2)
cl <- makeCluster(nCores)
registerDoParallel(cl)
setwd("/Users/a703402454/Desktop/UCSC_Project_Testing/Test_Data_Set_70%/TPM_Analysis")
Tumor <-
fread("Test_Set_TC... |
6d5ff04b9e8b8eee6da03d51efcc5349c86efeab | 607847657e271d3c5b505066d2983504a765e06e | /Code/RPackages/keyDriver/man/mergeTwoMatricesByKeepAllPrimary.Rd | 3e94f28cae4824a658ac8264980f6199cc848002 | [] | no_license | kippjohnson/RASNetwork | f7b513e0925297765224516b1e5d4e9d09d42a36 | 8a1a3a7ad6a9d1929e0e1238bc521bf6e740e54f | refs/heads/master | 2020-12-24T13:44:19.378865 | 2015-08-04T14:38:28 | 2015-08-04T14:38:28 | 39,347,327 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,635 | rd | mergeTwoMatricesByKeepAllPrimary.Rd | \name{mergeTwoMatricesByKeepAllPrimary}
\alias{mergeTwoMatricesByKeepAllPrimary}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Something
%% ~~function to do ... ~~
}
\description{
%% ~~ A concise (1-5 lines) description of what the function does. ~~
}
\usage{
mergeTwoMatricesByKeepAllPrimary(p... |
f44735b5d628c5414bb5ca9a487e1689c02f1f90 | 6390c203df735c874044a8ffa0f3692bf6010a6a | /man/Warehouse.Rd | a4f2c604e091ecb6bf018fed1b565734acb140bd | [
"MIT"
] | permissive | felixlindemann/HNUORTools | c8c61ec550e2c6673c8d3e158bd7bc21208b26ab | 0cb22cc0da14550b2fb48c996e75dfdad6138904 | refs/heads/master | 2020-05-15T18:37:48.423808 | 2018-02-04T11:04:52 | 2018-02-04T11:04:52 | 16,206,897 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,971 | rd | Warehouse.Rd | \docType{class}
\name{Warehouse}
\alias{Warehouse}
\alias{Warehouse-class}
\title{The Warehouse class}
\description{
This class is part of the \pkg{HNUORTools}. It represents
the base class for every locateable class in an
\dfn{Operations-Research (OR)}-context.
}
\details{
Find here the defined slots for this class.
}... |
7a1b8015fae1ce8c856c587b0b4ecbdc0a8ba914 | a992dc5179eebb2779e63a6284ef64bf6b22904d | /man/memoiseCache.Rd | eed7d964d1c6669f61a0dc369d3ffeced09a45ad | [] | no_license | philliplab/yasss | 707e1029bfc6054de2d6de933761b6e044123f5b | 20a53fda82c9019438ee4067cb7c6e87aca6aeaa | refs/heads/master | 2021-06-05T09:45:23.338398 | 2020-09-07T14:39:02 | 2020-09-07T14:39:02 | 146,469,843 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,003 | rd | memoiseCache.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/memoiseCache.R
\name{memoiseCache}
\alias{memoiseCache}
\title{Cache a function call with an associated seed value}
\usage{
memoiseCache(fun, args, cacheNamePrefix = NULL, seed = NULL, ...)
}
\arguments{
\item{fun}{The name of the function to... |
34c9cb33f28394e4ddefc9bf443d27c1687126b4 | b72e0d0d9d3b25d4909c4893c0b2db16843d8e0c | /plans.R | 8e3ae3df3f3cd8fdf1ddca2864b50536297315ab | [] | no_license | zaintejani/FinTech_Impulse | 765528d87a555049eb6bae7eb032ec3b0d43c78a | c290edf7622cd9dc2b97a357ebd115d025c8a378 | refs/heads/master | 2021-01-10T00:58:35.183111 | 2015-11-10T02:15:50 | 2015-11-10T02:15:50 | 45,881,130 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 430 | r | plans.R | ## Algorithm Skeleton:
## Account is the User.
## Tie transaction data to User using account ID variable
## Build transaction history (date: as Posixct)
## order containers by absolute freq, relative (recent) freq (date sub-filter)
## Remove lending style containers.
## Match "most preferred" containers by User to "... |
3717c67cf2ed7672083f2feb4cb794b0a7ab0617 | 13867cf2f13f520a0ab24227a47b53b5a74a2a4c | /Dropbox/HD-Quintana/CQuintana/Coursera/complete.R | 0f691c87ccfaaeb6549fdcc9d28ad8dac2e28cdb | [] | no_license | cquintanam/Coursera-Exm-2 | 7ac3c19b6e1d5a31c7d514221cd1d0ed76a7dd42 | de11da370585b32ea57c5b69ee8fdbda34d66e34 | refs/heads/master | 2023-04-02T21:00:04.360529 | 2021-04-06T03:51:10 | 2021-04-06T03:51:10 | 310,116,372 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 295 | r | complete.R | setwd("//Users//administrador//Dropbox//HD-Quintana//CQuintana//Coursera")
complete <- function(directory, files = 1:332)
{
dat <- data.frame(id = 1:332)
for(i in 1:332)
{
dat$nobs[i] <- dim(na.omit(read.csv(list.files(directory, full.names = TRUE)[i])))[1]
}
data = dat[files,]
return(data)
}
|
934cf5ba5d443fe630ea098e50ec33784d447ba1 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/coreCT/examples/rootSize.Rd.R | b0ac175c3c88491d87f327c9054f0a7f1426f2ac | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 963 | r | rootSize.Rd.R | library(coreCT)
### Name: rootSize
### Title: Convert a matrix of semi-processed DICOM images to root particle
### counts, volumes, and surface areas
### Aliases: rootSize
### ** Examples
ct.slope <- unique(extractHeader(core_426$hdr, "RescaleSlope"))
ct.int <- unique(extractHeader(core_426$hdr, "RescaleInterce... |
1dbf948c6b50186eb769ef756afb542b72280704 | 2e8fcc79e61ed9f80673834834fcf2abb4b8ac75 | /R/zzz.R | 49eef129bed5774dbb48ff028a3732cb62540052 | [
"MIT"
] | permissive | nickmckay/GeoChronR | 893708e6667ee898165c208d200f002063e6d83f | f37236e1fa6616f55798bbd4e1530b5b564d0f53 | refs/heads/master | 2023-05-24T01:32:59.690518 | 2023-01-17T23:16:47 | 2023-01-17T23:16:47 | 32,468,418 | 30 | 2 | MIT | 2023-01-19T17:46:24 | 2015-03-18T15:50:12 | R | UTF-8 | R | false | false | 199 | r | zzz.R | .onAttach <- function(...){
if(!interactive()){
packageStartupMessage(
cat(crayon::bold(glue::glue("Welcome to geoChronR version {utils::packageVersion('geoChronR')}!")),"\n")
)
}
} |
62ff32f1ad9d1c7b2cf7bf64c56962a28646b4b2 | 399d8ec2a319ba33da29c819964d32660ccff1c2 | /CleanData.R | d5d7259aa139c31fe3b0c96b607c148cbeb85261 | [] | no_license | thuggeanalyst/University-Ranking-R-Shiny | 90224a796ad7082a36197750f8381e417e5b5f46 | 21154e03cb2e7ba8217ce480da7332f49b853271 | refs/heads/main | 2023-07-01T12:47:44.463220 | 2021-07-31T18:38:35 | 2021-07-31T18:38:35 | 391,436,583 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 330 | r | CleanData.R | na_count1 <-sapply(timesData, function(y) sum(length(which(is.na(y)))))
na_count1 <- data.frame(na_count1)
na_count1
str(timesData)
timesData$world_rank<-as.numeric(timesData$world_rank)
timesData$total_score<-as.numeric(timesData$total_score)
#timesData<-na.omit(timesData)
timesData$year<-factor(timesData... |
7fef9f42f042eb1be43cd1f5975baada1bb9511f | 29f8f3ee59c366ea408633d183614bc39b49b26d | /Duke_DGHI/[DUEM] US_3DUSsamplesize_code.R | 9b5d255cc02edcf66a33f3eb534ac6a4a3060370 | [] | no_license | souzajvp/analytical_codes | 92db345dc75f128c2f25fb7b28f0891139ffea98 | dcc49662253ba1dbd4f54b8c4caea40232632783 | refs/heads/master | 2023-05-23T06:06:12.058469 | 2021-06-07T18:11:00 | 2021-06-07T18:11:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,685 | r | [DUEM] US_3DUSsamplesize_code.R | install.packages("MKmisc")
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("limma")
library("MKmisc")
## see n2 on page 1202 of Chu and Cole (2007)
power.diagnostic.test(spec = 0.70,
delta = 0.10,
power = 0.80,
sig.level=0.05,
... |
5b929eba6a2e7a3766c214fd5cdc0dc2c81f6c5a | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/FactoMineR/examples/print.catdes.Rd.R | 35be80a6cf2bcd5653a41368ee0504a1689b5283 | [] | 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 | 242 | r | print.catdes.Rd.R | library(FactoMineR)
### Name: print.catdes
### Title: Print the catdes results
### Aliases: print.catdes
### Keywords: print
### ** Examples
## Not run:
##D data(wine)
##D res <- catdes(wine, num.var=2)
##D print(res)
## End(Not run)
|
e28d8b862c9618863a665d7eb4412631d66953ce | 48bcbc2f996f4afe02f39b9a033810dced553c67 | /data/OpenWeatherMap.R | c0c01fecdb2f3fd10faa8d33d2d681a82a6276fd | [] | no_license | dstoiko/hackathon-datapower | 2731eba0ca05551d6f6e2baee7787365258c89d1 | 07151b8224c0fdba4f914860db063dc121fec01b | refs/heads/master | 2021-01-16T23:21:40.667280 | 2016-06-27T12:04:21 | 2016-06-27T12:04:21 | 61,956,685 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 208 | r | OpenWeatherMap.R | ### OpenWeatherMap Data API call
library(ROpenWeatherMap)
key = "5a3167b76fef776330af151a62afba29"
data=get_current_weather(api_key=key,city="paris")%>% as.data.frame()
temperatureC = data$main.temp - 273.15 |
524c2f082cab9951db964a23b7f9bb5b87076966 | 3824d9a06dede35d38c1e9a80375c131cf4e502f | /man/tdi.Rd | bf67e2c088b85e3c402b47cf85a9f3c973e5f560 | [] | no_license | king8w/diathor | 1b8b39b21402c7fc3d49a714362b183b9ddafd0b | 5b0e529fb24ca8f36acabd3923b6782c113c939a | refs/heads/master | 2023-03-07T14:57:46.827205 | 2021-02-24T04:50:06 | 2021-02-24T04:50:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 581 | rd | tdi.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\encoding{UTF-8}
\name{tdi}
\alias{tdi}
\title{TDI}
\format{
A data frame with the ecological values for 3445 species
}
\source{
\url{https://link.springer.com/article/10.1007/BF00003802}
}
\usage{
data(tdi)
}
\descripti... |
81ac01a0c2b78f766a1fa88ad3e5e18d33ff8655 | af28d2289d826d08e2c1e61be84e470988976848 | /man/combinatorics.add.parameter.Rd | 12f2b309bf998b605e9312024be8981698386142 | [] | no_license | mbich/combinatorics | 6ed3b0f256b831f3e7337fea0bd22bf1a3e06705 | c46212d477c02e0608ff9226697fe517f958c4af | refs/heads/master | 2020-12-02T18:05:52.525420 | 2017-07-09T19:52:46 | 2017-07-09T19:52:46 | 96,470,307 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 6,184 | rd | combinatorics.add.parameter.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/combinatorics.design.add.R
\docType{methods}
\name{combinatorics.add.parameter}
\alias{combinatorics.add.parameter}
\alias{combinatorics.add.parameter,Combinatorics,character,character,numeric,missing-method}
\alias{combinatorics.add.paramete... |
eaf4ad2ad3c71a6bb361823902a7009e5e39dce5 | 689635789d25e30767a562933f39fcba1cebecf1 | /Alpha Modelling/QuantStrat/Packages/IKTrading/demo/stepwiseCorRank.R | 369b57a8792396347907ba2d675a90f7287e2902 | [] | no_license | Bakeforfun/Quant | 3bd41e6080d6e2eb5e70654432c4f2d9ebb5596c | f2874c66bfe18d7ec2e6f2701796fb59ff1a0ac8 | refs/heads/master | 2021-01-10T18:23:23.304878 | 2015-08-05T12:26:30 | 2015-08-05T12:26:30 | 40,109,179 | 5 | 0 | null | 2015-08-05T12:12:09 | 2015-08-03T06:43:12 | R | UTF-8 | R | false | false | 3,181 | r | stepwiseCorRank.R | stepwiseCorRank <- function(corMatrix, startNames=NULL, stepSize=1, bestHighestRank=FALSE) {
#edge cases
if(dim(corMatrix)[1] == 1) {
return(corMatrix)
} else if (dim(corMatrix)[1] == 2) {
ranks <- c(1.5, 1.5)
names(ranks) <- colnames(corMatrix)
return(ranks)
}
if(is.null(startNames)) {
... |
fc1f2eb3fb4899fc9696459e1bb703b0ad4a7ef4 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/bqtl/examples/residuals.bqtl.Rd.R | dc577bd15f2bcbdc1d3eee039a8637d61e085213 | [] | 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 | 385 | r | residuals.bqtl.Rd.R | library(bqtl)
### Name: residuals.bqtl
### Title: Residuals from QTL models
### Aliases: residuals.bqtl
### Keywords: methods
### ** Examples
data(little.ana.bc)
fit.pheno <- bqtl(bc.phenotype~locus(15)+locus(42),little.ana.bc)
summary(residuals(fit.pheno))
plot( fitted( fit.pheno ), residuals( fit.pheno) )
##... |
a20e474fef7247c5e1c92be4b4ad02989b875180 | e661887eb7058f962333e4dfb5887c42ffe4891b | /plot1.R | 25ecc97457359e3ed40580396aa01687cdda25cd | [] | no_license | Rastermyosin/ExData_Plotting1 | 31391afd587e287affe9b72dfe65184b7ba69d2e | 17710b3653143dcbf90ac004c38bb9736b9f4ef2 | refs/heads/master | 2020-11-30T23:34:31.924094 | 2015-03-08T23:10:03 | 2015-03-08T23:10:03 | 31,860,771 | 0 | 0 | null | 2015-03-08T18:40:36 | 2015-03-08T18:40:36 | null | UTF-8 | R | false | false | 705 | r | plot1.R | ############################################################
# Plot1: Histrogram of Global Active Power
############################################################
#### Load Data ####
data = read.csv(file = "./Data/household_power_consumption.txt", sep = ";")
# Subset Data #
dateTest = as.Date(data$Date,"%d/%m/%Y")... |
39991329d6484beabf9336957f54ff30d1932d6d | 113255ebb19fac37698d5897a96660977c4a9ca6 | /src/init_spatial.R | 272ded801c263230ab782e0e55dc09d83cd28e25 | [] | no_license | Ludwigm6/tRacking | e3f4fc69dc4b4144b2c282abe91417762f336c9a | abeda02ae1bf1fa3225221f96dfcc702815a82a5 | refs/heads/master | 2020-04-16T18:21:42.382018 | 2019-02-05T17:18:55 | 2019-02-05T17:18:55 | 165,816,300 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 861 | r | init_spatial.R | # rteu spatial init
library(rgdal)
library(mapview)
library(raster)
library(plyr)
source("~/repositories/envimaR/R/getEnvi.R")
p <- getEnvi("/home/marvin/rteu/field_test/data/")
s <- getEnvi("/home/marvin/rteu/field_test/scripts/")
# antenna as spatial
antennas <- read.csv(paste0(p$gps_data$here, "antennas.csv"... |
34d5bf607a1cc3a873502a46d8f2f0a32488eb7a | 2d39c37ead4338a40b263515a31b55ccc719fdf5 | /R/load_chromhmm_emissions.R | f6d735322fc16d674a57f034ea82fe31a759a3c1 | [
"MIT"
] | permissive | csiu/hmmpickr | b9f6a8d831f93c0a6a3753aad3c65bb079271da5 | eadb6476150c83086a245ae71754caa0066be2da | refs/heads/master | 2021-01-19T17:10:27.779925 | 2017-03-14T07:27:33 | 2017-03-14T07:27:33 | 83,733,732 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 369 | r | load_chromhmm_emissions.R | #' Load ChromHMM emission probabilities
#' @param filename The ChromHMM model emissions file
#' @param ... options for readr::read_tsv(...)
#' @export
load_chromhmm_emissions <- function(filename, ...) {
emissions_probs <- readr::read_tsv(filename, progress=FALSE, ...)
colnames(emissions_probs)[1] <- "state"
tidy... |
cc878c16e22d2a7526064cc1927eaa0e62c3f444 | 38c16978738ffac95bfcf1e78fcb243fc4195305 | /R/standardize.R | f9b86130dfd097db02761829f76fd60de288ac50 | [] | no_license | ebenmichael/balancer | ca3e2f733c52450d8e7b5b1a4ebd0d182713d4eb | 55173367e2c91f1a3ce47070f8430c6686a049bd | refs/heads/master | 2023-07-10T20:52:54.547666 | 2023-06-20T14:40:01 | 2023-06-20T14:40:01 | 129,783,286 | 7 | 3 | null | 2023-05-16T19:21:44 | 2018-04-16T17:47:11 | R | UTF-8 | R | false | false | 15,677 | r | standardize.R | ################################################################################
## Wrapper to standardize to target means
################################################################################
#' Re-weight groups to target population means
#' @param X n x d matrix of covariates
#' @param target Vector of po... |
24a805baf8d15b24990a259b703c76e409aec384 | 93ebef2e3663445bb5dc2de07569dadc31ef0325 | /R/plos_records.R | 2c90d386e5ce369808ab529b6bdef386eb1ed1a0 | [] | no_license | poldham/oldhammisc | 6817f9d3036583dea5a48a4b65e8d03c9bf8c343 | 63eb6fbc9a358525e17d444d8522ba0997bea265 | refs/heads/master | 2020-05-30T07:16:06.917686 | 2018-02-09T13:03:09 | 2018-02-09T13:03:09 | 59,103,337 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 966 | r | plos_records.R | #' @title Retrieve count of results for a query with PLOS
#' @description Use this function to work out how many results a query of PLOS using rplos will return. Useful for deciding on data to download.
#' @param query A search term or vector of search terms. For multiple terms use double quotes (see examples).
#' @ret... |
90d35149b0734a111702a49d1d74418de5469889 | d8f1ba7075531ef75a1f139a8da0bea02ab9c9fc | /R/data_script.R | fbe20342a4dcbc7728be39fe472854e22282260c | [] | no_license | jasonhilton/viz_weekly | 7b81d6c7df575ee993bf89969c022cf78035c004 | 80b1bda28445fc5e858dc4ab8015c5ad3675936c | refs/heads/master | 2021-06-27T15:39:12.378321 | 2019-06-14T13:00:39 | 2019-06-14T13:00:39 | 135,202,788 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,195 | r | data_script.R | library(curl)
library(dplyr)
library(tidyr)
library(ggplot2)
library(magrittr)
library(readxl)
library(purrr)
library(ggfan)
library(httr)
library(HMDHFDplus)
# 21st century mortality files.
# deaths by age, sex, year, and cause of death.
deaths_file <- paste0("https://www.ons.gov.uk/file?uri=",
... |
dc17e812ef8309c86c87a9a1da282d565e35b7f0 | a12c2a31361ec8b6fdc5ac9e73130801aec43e40 | /resmatch/man/create_text_corpus.Rd | 5667dd999966e29a3ea1773c0a35a131790c0718 | [] | no_license | wjburton/resume-matching | 143728174b7e0146e405b3a6f0c6d53dee45d04c | 2e0062a5f4ac0b490843f64cb1b0eedf31b24560 | refs/heads/master | 2021-01-13T08:07:33.688581 | 2018-01-16T22:06:43 | 2018-01-16T22:06:43 | 71,744,820 | 4 | 2 | null | null | null | null | UTF-8 | R | false | true | 499 | rd | create_text_corpus.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils.R
\name{create_text_corpus}
\alias{create_text_corpus}
\title{Uses tm_package to clean a resume or vector of documents.}
\usage{
create_text_corpus(text)
}
\arguments{
\item{text}{= a resume or vector of documents}
}
\value{
a Vcorpus/C... |
3d37fdd7d7abf70fb51f6471a7e61b6b3710e49f | f77d4ae139d960f6138e29f4e5e9e39fcba528fb | /R_CODES/masters_project/Parallelize_code_in_R.R | 44e2834e6a8e62495464eab5e310ee517d7ea6b5 | [] | no_license | zenabu-suboi/masters_project | fc80eb077af8e92bf81cda94952d4dec196bb263 | d865eb68e66d35c52229023d7aa83b78fd7518f4 | refs/heads/master | 2022-04-22T15:01:15.063667 | 2020-04-28T10:50:17 | 2020-04-28T10:50:17 | 179,095,292 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,433 | r | Parallelize_code_in_R.R |
#################################################################################
setwd("C:/Users/ZENABU/Documents/GitHub/masters_project/R_CODES/masters_project")
source("my_functions.R")
#################################################################################
###############################################... |
85019376f9b462357314ccdf28d3a6a126786c3b | 5db34fe55462f237703358e5ead7c80299de3d02 | /R/powerUntransform.R | 0165dbaa8b9ad4dd27a1beb5add1e6e832c3005a | [] | no_license | cran/tlm | 687fe4cb6d25a1086f46e61afb5faa898037f9e2 | 4a399dc84a6b38f8681ef4709c14115d89505f27 | refs/heads/master | 2021-01-17T07:11:00.175043 | 2017-04-10T12:15:19 | 2017-04-10T12:15:19 | 23,803,445 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 104 | r | powerUntransform.R | powerUntransform <-
function(xt, power)
{
if (power == 0) x <- exp(xt) else x <- xt^(1/power)
x
}
|
5092b6a3a6e0236f86ff49cd951461ca79bd1d32 | fd0622e97276bba2c04d3c2fcba902cdfb65e214 | /packages/nimble/inst/classic-bugs/vol1/bones/bones-init.R | 36c66ae5b4da45a59b8c6e008a439a9b2f7c730a | [
"GPL-2.0-only",
"BSD-3-Clause",
"CC-BY-4.0",
"GPL-1.0-or-later",
"MPL-2.0",
"GPL-2.0-or-later"
] | permissive | nimble-dev/nimble | 7942cccd73815611e348d4c674a73b2bc113967d | 29f46eb3e7c7091f49b104277502d5c40ce98bf1 | refs/heads/devel | 2023-09-01T06:54:39.252714 | 2023-08-21T00:51:40 | 2023-08-21T00:51:40 | 20,771,527 | 147 | 31 | BSD-3-Clause | 2023-08-12T13:04:54 | 2014-06-12T14:58:42 | C++ | UTF-8 | R | false | false | 1,888 | r | bones-init.R | "theta" <-
c(0.5, 1, 2, 3, 5, 6, 7, 8, 9, 12, 13, 16, 18)
"grade" <-
structure(c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N... |
9bc48189d052d5adfc92f1fe4e268e574af7a8f7 | 790e5f064a41aac88f3465591158a73e6faaec77 | /R/parameters.R | 4a3442357d805f81c3aa3242e64e45159ca8066a | [] | no_license | cristianmejia00/heatmaps3 | 033a08c786d2dc4e3caebdbb0431f756ebf7c33a | 763850d8f2d640d51f0dea950596330aecc236f8 | refs/heads/master | 2020-06-20T07:49:33.950688 | 2017-06-14T10:19:40 | 2017-06-14T10:19:40 | 94,198,532 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 435 | r | parameters.R | # Write names for the Output files
similarity_matrix <- "heatmap_matrix.csv" #The similarity matrix based on cosine similarity
edge_list <- "heatmap_list.csv" #The Top pairs of topics - clusters
heatmapTC <- "heatmap.png" #Heatmap image of the similarity matrix
######################################################... |
25d749ce3920ba47f79cdd9d16b28e658296fb26 | 84e7b589d3d8b05e52e927dc7ce77b79515e71fa | /ch11 - 회귀분석/04..로지시틱 회귀분석.R | 521b9f1b4a3069c6ba5edaa8a4564fc676b9c691 | [
"MIT"
] | permissive | Lee-changyul/Rstudy_Lee | d1e0f28190de74643d5c0a14f178b41250db7860 | 837a88d6cb4c0e223b42ca18dc5a469051b48533 | refs/heads/main | 2023-06-29T20:21:10.968106 | 2021-08-02T01:48:00 | 2021-08-02T01:48:00 | 325,493,003 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,114 | r | 04..로지시틱 회귀분석.R | #### 04.로지스틱 회귀분석(Regression) #####
# 01.데이터 불러오기
lreg.df <- read.csv("Ch1104.로지스틱회귀분석(LREG).csv",
header=TRUE,
na.strings = ".")
lreg.df$exp <- factor(lreg.df$exp,
levels=c(0:1),
labels=c("No","Yes"))
lreg.df$chun <- factor(lre... |
ef88f9812340076ceb2df0323f5416c99081bb9b | a3541fa9afdcbc4bd1360afda4b6f8d170244889 | /data-raw/vars-ejscreen-acs.R | d56fc7ddb3bc59b3cf6e1e11790ed8103066436e | [] | no_license | ejanalysis/ejscreen | 4349236260c94dd9a9d0cfdcae237adebcec2d8a | 6af10b7d3b47c683cb512fd4792c2eef0e1d695a | refs/heads/master | 2023-05-27T11:59:13.144072 | 2023-05-25T23:40:52 | 2023-05-25T23:40:52 | 40,103,218 | 7 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,137 | r | vars-ejscreen-acs.R | ## code to prepare `vars.ejscreen.acs` dataset
# mytables <- c("B01001", "B03002", "B15002", 'B23025', "B25034", "C16002", "C17002")
# get.table.info(mytables)
# ID title
# 1 B01001 SEX BY AGE
# 2 B0300... |
6ff071a7b8359d436d6c5b98b2f810c950b767ae | a44839546bb036ae0a8c086595cc8babe9f16ace | /man/getFinalDispersions.Rd | 8de171efc21ba1495ce3c89e92acaf5c027d422d | [
"MIT"
] | permissive | eachanjohnson/concensusGLM | 6ba2219890ea93e39a15e4be16c07140ec63787e | 6d310a4bd15116306c9c2395ac73dd48672b4356 | refs/heads/master | 2021-06-11T19:02:50.535116 | 2019-06-24T18:12:11 | 2019-06-24T18:12:11 | 45,924,291 | 2 | 0 | MIT | 2019-06-24T18:12:12 | 2015-11-10T16:21:30 | R | UTF-8 | R | false | true | 1,783 | rd | getFinalDispersions.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/concensus-statistical-methods.R
\name{getFinalDispersions}
\alias{getFinalDispersions}
\alias{getFinalDispersions.concensusDataSet}
\alias{getFinalDispersions.concensusWorkflow}
\alias{getFinalDispersions.default}
\title{Estimate Negative Bin... |
8901f09ffc7d93249fd97b1ab5ad8105b2f47c0c | 34ba13f4b49f2abbd059f2de1bccecd5564e4708 | /fungicide.app.R | 544b05ebd6ae662067867f278d2f54d4480b78ee | [] | no_license | sithjaisong/SKEP2DB | e8ce62275a7256934802db6571f2e39dd010ef8c | 9a0bd831661f81e06b33613888ab9f24032f9304 | refs/heads/master | 2021-01-21T13:17:37.000088 | 2016-04-25T02:34:57 | 2016-04-25T02:34:57 | 43,069,491 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,738 | r | fungicide.app.R | data <- all.pesticide %>%
filter(location == "IDN" & season == "DS") %>%
select(location, year, season, fno, fung, fung.dvs) %>%
group_by(location, year, season, fno, fung, fung.dvs)%>%
filter(!fung == "0" ) %>%
summarise(n.fung.app = n()) %>%
ungroup() %>%
arran... |
72f46c41e38b65ba4a21e10932ceab43269a096c | f9010a6b4f7d042b27e0952a04f1c76e23243e8f | /src/003_validation.R | 0435428dc9f8025bc56abe978bc250132dfc4dbe | [] | no_license | envima/ForestModellingRLP | 0690223c0c7f81043122e5eb9922bb61904244b1 | 944dd07d1ae4245537bf67862e9ebb6a1f2e9034 | refs/heads/master | 2022-12-08T01:32:14.843785 | 2022-11-29T15:18:07 | 2022-11-29T15:18:07 | 244,846,593 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,030 | r | 003_validation.R | #' @name 003_validation.R
#' sub control script for data preparation
#'
#'
#' @description Use this script for controlling the processing.
#'
#' @author [name], [email@com]
#'
# 0 - set up ####
#---------------#
library(envimaR)
library(rprojroot)
root_folder = find_rstudio_root_file()
source(file.path(root_folder, ... |
bf50e15a34c8856d4d139562e63f9d7823ecaef3 | d2e738d6d32a9f5ffbd14f2bada4dc734a8340f2 | /case_studies/VMJG2018/data/OrigLevyKellerData/prediction_experiment_data/experiment2/lmr/scripts/analyze.R | 7698b6abc2447494b8c957e1aed0db0e17a1458c | [
"MIT"
] | permissive | vasishth/IntroductionBayes | 703766c08385c7751c98214ca70b28415b3885d7 | 739bcabc527b18c050d22d62eebeace88bbca1b5 | refs/heads/master | 2020-04-29T11:47:52.796613 | 2020-03-10T15:40:53 | 2020-03-10T15:40:53 | 176,113,078 | 44 | 14 | null | null | null | null | UTF-8 | R | false | false | 8,719 | r | analyze.R | #condition dat adj
#a sub sub
#b sub main
#c main sub
#d main main
library(lme4)
cat('########## EXPERIMENT 2 ##########\n\n')
cat('########## REGION 8 ##########\n\n')
cat('# First fixation\n\n')
reading_time <- read.table('exp3_1fx_r.res', header=TRUE)
reading_time$... |
1a65936d4031e428f3e31d637885580a4409286b | e23426737bf92cb62b1d0136b410b8dc4e5c213c | /scripts/00.readData.R | 5e83967540a57e816e35d2cbfc55160b4bd27517 | [] | no_license | andrew-hipp/white-oak-syngameon | 9018fe0477743e631d77621ca552501dfa82719d | d5f85b96be2ca2957bb3cfd9fb1ec9641666d42b | refs/heads/master | 2020-04-11T08:49:01.518742 | 2019-08-09T21:08:16 | 2019-08-09T21:08:16 | 161,656,789 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,990 | r | 00.readData.R | ## merge 2017 OAKCODING data with 2018 Sequenom data
## format for analysis
library(openxlsx)
library(Biostrings)
library(magrittr)
library(adegenet)
if(!exists('haversine')) source('https://raw.githubusercontent.com/andrew-hipp/morton/master/R/haversine.R')
indsThreshold <- 0.9 # proportion of individuals r... |
2d514dcccbd1ae9570d3f7a8faf68fe440a4eac6 | d34bd74c59358c0eb0cf927bbee8551d1e7eed97 | /src/2020/day1_solution.R | 1c2455bea6fd8eac35519d96945d262650796912 | [] | no_license | bradisbrad/advent_of_code_2020 | 7dc50174cc047945c4119df83f176e240bc7bd25 | 5cc0ee78ee6c44e517420e65d9f234135de30b5d | refs/heads/main | 2023-01-24T18:54:52.928004 | 2020-12-04T04:27:11 | 2020-12-04T04:27:11 | 318,323,908 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 638 | r | day1_solution.R | # Q1: Find the two entries that sum to 2020 and return the product
# Q2: Find the three entries that sum to 2020 and return the product
library(tidyverse)
library(here)
data <- read_tsv(here('data/2020/day1_input.txt'), col_names = F)
a1 <-
expand_grid(data,
rename(data, X2 = X1)) %>%
mutate(sm ... |
c0a6ccd8b23f33c726d70a59d06a878f9120f531 | f97987c497e5d0aade2b4057f54915af25e25090 | /run_analysis.R | 85d5d775a19ed2d3e09ae4ee22f640d10c7400d8 | [] | no_license | jptodd/Getdata-031 | e14f1083d2858a0462613eb09524f2838608f502 | cf46b2d7711305474c5ff1176349e4780ba4785f | refs/heads/master | 2016-09-05T10:07:40.223163 | 2015-08-23T23:13:18 | 2015-08-23T23:13:18 | 41,269,495 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,085 | r | run_analysis.R | # getdata-031 project
# Uses dataset published in
# [1] Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz.
# Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine.
# International Workshop of Ambient Assisted Living (IWAAL 2012). Vitori... |
e42a5670ce4622bf16ce406a4b1e147a4b105b54 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/stochprofML/examples/toycluster.LNLN.Rd.R | bb27e4b24d8ee4c8819f6eac48e1da1bafb888dd | [] | 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 | 422 | r | toycluster.LNLN.Rd.R | library(stochprofML)
### Name: toycluster.LNLN
### Title: Synthetic data from the LN-LN model
### Aliases: toycluster.LNLN
### Keywords: datasets synthetic data stochastic profiling
### ** Examples
data(toycluster.LNLN)
par(mfrow=c(3,4))
for (i in 1:ncol(toycluster.LNLN)) {
hist(toycluster.LNLN[,i],xlab="synthet... |
1b4541ced1d21953faf1795f2d9ef43c9ab49ba5 | 7a9b8f6512e497bab53e579ede4814c18d92d562 | /helper.R | 3e8db049ffaa6c3458f079c24ad783533463f7a2 | [] | no_license | slowbro1/thomson_reuters_paint | 4f203d5cd71dfd9912a338d4207cde9f5f022db0 | f608c0640976b69f4bca56dd48554f7feb0dcb39 | refs/heads/master | 2020-12-31T04:29:13.771534 | 2016-04-01T18:39:09 | 2016-04-01T18:39:09 | 55,251,912 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,446 | r | helper.R | #Helper
url<-"https://dev.api.thomsonreuters.com/eikon/v1/timeseries?X-TR-API-APP-ID=r5LjbEgTGh3ZBYumNIhN8qvut7r9p2oW"
jsquery <-
'{
"rics": ["IBM.N"],
"interval": "Daily",
"startdate": "2015-10-03T00:00:00Z",
"enddate": "2015-12-07T23:59:59Z",
"fields":
["TIMESTAMP","OPEN","HIGH","LOW","CLOSE","VOLUME"... |
bffed66e146e82f9b3c4f03365b733c48fe4cc8c | d28aac84af4b538137205c9afe8764c6c7dd0911 | /extract-microarray-data.R | 6aacb6f5817d0bf27ff1fdad460a23e170dcfb36 | [] | no_license | ClaireLevy/HVE-microarray | 9c67a92b8168ca9fd4aa34d77137d817f38013d1 | ca21449cea883e1daf12083a987f63bef84f6b65 | refs/heads/master | 2021-01-19T08:10:18.544493 | 2015-11-19T23:29:25 | 2015-11-19T23:29:25 | 30,942,256 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,388 | r | extract-microarray-data.R | folder <- "J:\\MacLabUsers\\Claire\\Projects\\HVE-microarray\\microarrayData\\"
file <- readLines(paste0(folder, "FinalReport_exvivo_TNF_HVE.txt"))
# File structure
# Line 1: [Header]
# 2-7: Header details
# 8: [Sample Probe Profile]
# 9: Column names
# 10-47332: Microarray data
... |
9f11c4e5b746f4f3d99bb2a5b810f18da9f00a3e | 7b99e0516455a5e61f010dd7015da2461117263e | /inst/tinytest/test-ergmito-checkers.R | f9f07d7ed2e2d6e140c85e2864ae5deba6faabe8 | [
"MIT"
] | permissive | muriteams/ergmito | 75ec8830de7bcf47250c2038f418123eb9fc9c9e | f3a2ede1ed3a97eaed71987ec5b555a853cbd11d | refs/heads/master | 2023-06-25T08:57:37.368032 | 2023-06-13T19:46:18 | 2023-06-13T19:46:18 | 157,758,250 | 9 | 1 | NOASSERTION | 2020-07-06T05:17:20 | 2018-11-15T18:56:47 | R | UTF-8 | R | false | false | 1,297 | r | test-ergmito-checkers.R |
# Fully connected network
x <- rbernoulli(c(4,4,4), 1)
ans0 <- ergmito(x ~ edges + ttriad)
# Very high density
x <- lapply(x, function(x.) {
x.[2] <- 0L
x.
})
ans0b <- ergmito(x ~ edges + ttriad)
ans0b$formulae$loglik(c(1e3, coef(ans0b)[2]))
# Empty graph
x <- rbernoulli(c(4,4,4), 0)
ans1 <- ergmito(x ~ edges + ... |
44be8a58df4d3ce27fbbccad3ad232d93fef8bf5 | b0e6d906265d8eec88232193b424e2eca3a9f4bc | /functions/get_lift_and_leverage.r | 1792f0427a013e2f3ba9bcc7a2cb4e25e2a1eb67 | [] | no_license | EL-SHREIF/Apriori-Algorithm | 0bc6cbe8c715b09e3fc12c655f69485e88cdd0fa | 85603a87eb3b653590d1bdbe6d2395639760d6fe | refs/heads/master | 2022-10-28T20:32:54.933716 | 2020-06-14T16:50:47 | 2020-06-14T16:50:47 | 257,570,820 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 968 | r | get_lift_and_leverage.r | get_lift_and_leverage <- function(rules, supports){
lifts_leverages = matrix(ncol=2)
colnames(lifts_leverages) = c('lift', 'leverage')
for (rule in rules){
left_right = strsplit(rule, split = '/')
left = strsplit(left_right[[1]][1], split = '-')[[1]]
right = strsplit(left_right[[1]][2], spl... |
fdee2fd996b261a14c05471582443769c7537d77 | 358842d28556f07557977e228a82b9014ddd08ab | /R/write_stat_results_omics.R | d7e711558ab9f7dd74ce10ff141100972c19a74b | [
"BSD-2-Clause"
] | permissive | rarichardson92/pmartR | 519ccc42936e1735850c2ce9a8cbbe34fe2d83e0 | cbae3a82fd923359f11c7ba6cb726a88d6855301 | refs/heads/master | 2021-07-17T11:24:54.068489 | 2020-07-08T21:19:25 | 2020-07-08T21:19:25 | 185,486,874 | 0 | 0 | BSD-2-Clause | 2019-10-11T15:47:41 | 2019-05-07T22:28:41 | R | UTF-8 | R | false | false | 4,019 | r | write_stat_results_omics.R | #' Creates a list of three sheets, Normalized Data, DA Test Results, and Only DA biomolecules - for OMICS project
#
#'
#' @param omicsData an object of one of the classes "pepData", "proData", "metabData", or "lipidData", usually created by \code{\link{as.pepData}}, \code{\link{as.proData}}, \code{\link{as.metabData}}... |
d90a67f0d1ecb25bb0442aee428e5d7305265eb8 | 863aa7e71911423a9096c82a03ef755d1cf34654 | /man/get_metadata.Rd | af9088780d7c87781f98cac549c7f61c4036e99c | [] | no_license | BioSystemsUM/specmine | 8bd2d2b0ee1b1db9133251b80724966a5ee71040 | 13b5cbb73989e1f84e726dab90ff4ff34fed68df | refs/heads/master | 2023-08-18T05:51:53.650469 | 2021-09-21T13:35:11 | 2021-09-21T13:35:11 | 313,974,923 | 1 | 1 | null | 2021-09-21T13:35:12 | 2020-11-18T15:22:49 | R | UTF-8 | R | false | false | 723 | rd | get_metadata.Rd | \name{get_metadata}
\alias{get_metadata}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Get metadata
}
\description{
Get the metadata from the dataset
}
\usage{
get_metadata(dataset)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
\item{dataset}{
list representin... |
3c9113409df80c1aaff7adbfaa58db1400061ab4 | 7adb1775672fb7b320ad9da1bb3f1edeb8d33f0d | /archive/regardvapanalysis_iv ver 2.0 10 August (with group sequential).R | 037341a37e6221744ffbdf3a7df72169f90a099e | [
"CC0-1.0"
] | permissive | vitallish/NItrialsimulation | 0a60b60bd053a8c2e1e92954c69562ff4c15bff4 | ef7f1e6e934440e8c7bc5e3a8293988051dd4b3f | refs/heads/master | 2022-04-12T04:41:17.880021 | 2020-04-06T11:45:39 | 2020-04-06T11:45:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 42,322 | r | regardvapanalysis_iv ver 2.0 10 August (with group sequential).R | ########################################################################
###################Simulation for REGARD-VAP analysis###################
########################################################################
setwd("/Users/moyin/Desktop/VAP studd/Causal inference simulation") #set working directory
rm(list=... |
6d770c9845e4e240329e91e07b6c19585ccf13b6 | b229db462a31f45d0ea7258fd53e988f5f334fd2 | /man/circle_points.Rd | e118b3647f7855c1259d89074b835d958917eca2 | [] | no_license | fdzul/hotspotr | 08bc4384393a0f2042ff75d79628436632f59cfe | e370aa52c92b2e4b0d54d7825ef3865da3d14154 | refs/heads/master | 2020-07-15T11:44:50.753458 | 2014-07-18T14:31:04 | 2014-07-18T14:31:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 571 | rd | circle_points.Rd | % Generated by roxygen2 (4.0.1): do not edit by hand
\name{circle_points}
\alias{circle_points}
\title{Surround a set of points with a circle of points at a pre-specified
radius.}
\usage{
circle_points(x, y, np = 6, r = 0.5)
}
\arguments{
\item{x}{vector of x coordinates for points to surround}
\item{y}{vector of y co... |
58ae017c62131e1451758b87dbef0f6b37ca233e | d943eb5047ad9fa312170bb644129aa8d8e420c1 | /inst/AOV2R/AOV2R.R | f9955a5a5a367b1e0f5b03bdb63204d2ccd85635 | [] | no_license | stla/gfilmm | 3e85e1da4dc6127aec16fd910ddcc4ae0be668b5 | 865f3d5854b35db3fc956e98d38883ef4681e745 | refs/heads/master | 2022-07-28T10:14:50.453119 | 2022-07-11T17:43:58 | 2022-07-11T17:43:58 | 150,234,446 | 0 | 1 | null | 2021-06-25T09:45:57 | 2018-09-25T08:47:25 | C++ | UTF-8 | R | false | false | 4,328 | r | AOV2R.R | library(rgr)
SimAOV2R <- function(I, J, Kij, mu = 0, sigmaP = 1, sigmaO = 1, sigmaPO = 1,
sigmaE = 1, factor.names = c("Part", "Operator"),
resp.name = "y", keep.intermediate = FALSE) {
if (length(Kij) == 1L) {
Kij <- rep(Kij, I * J)
}
Operator <- factor(
rep(spr... |
843cfb90252c57c6cc7ebeebf77af89bb6ada036 | ae163aa2bd49c395807ef273f0d4f6dcce2956d6 | /man/my_csv_reader.Rd | c7655e501487caa2dc6dc6539bb0485ea1c2f43a | [] | no_license | samimhirech/finalpackage | 6361d0a24846b87e21c867a9d10f3a0a7a50b086 | 2470e0a2231397ab0cf6cfb6e405e960cea19698 | refs/heads/master | 2021-05-08T09:09:55.207313 | 2017-10-16T08:50:11 | 2017-10-16T08:50:11 | 107,099,665 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 283 | rd | my_csv_reader.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/my_csv_reader.R
\name{my_csv_reader}
\alias{my_csv_reader}
\title{My csv reader}
\usage{
my_csv_reader(x)
}
\arguments{
\item{x}{a path}
}
\value{
this returns the csv file
}
\description{
My csv reader
}
|
f0ad83b84e1cd12bc518b55342321cab1cd76c5e | a3ea56f1ab54e0c3d5b794b9ab358870c3e03444 | /man/ringo.Rd | 665cb40ef8b951a56d43674f408a2868c909ce79 | [] | no_license | jameswagstaff/ringo | 511acf849fac21705aa4775a10038c0d3672da64 | f54b682eca422a47a6a97e29db53831740237200 | refs/heads/master | 2021-08-16T01:04:28.769229 | 2020-04-29T16:53:35 | 2020-04-29T16:53:35 | 170,023,663 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 355 | rd | ringo.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ringo.R
\docType{package}
\name{ringo}
\alias{ringo}
\title{ringo: Read STAR files into R}
\description{
The ringo package is for reading and manipulating STAR files like those generated by
Relion \url{https://www2.mrc-lmb.cam.ac.uk/relion/in... |
dd6364b2f3a7b64debc60bbd0897226dcd155521 | 808279a6a210ccf9bdc76eafbb2938b83c88aafc | /R/subscripts/palaeorotation_sensitivity_test.R | 4e321cceadb9e0c36feb04db7c29063fa93aa6f1 | [] | no_license | LewisAJones/Coral_Reef_Distribution | a4a87261b126e0350a2a897d464e672aa34708b4 | a746fe7ca15d22b0d385e6e200b3c6d0689ca7e9 | refs/heads/main | 2023-04-10T02:00:48.567855 | 2022-06-15T18:26:33 | 2022-06-15T18:26:33 | 351,208,167 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 905 | r | palaeorotation_sensitivity_test.R | #load libraries
#sensitivity between models
library(chronosphere)
library(dplyr)
#collection_no 34647 coordinates
xy <-cbind(long=c(74.6667), lat=c(37.3333))
#approx. mid age of collection
age <- 218
#try different rotation models
models <- c("PALEOMAP", "MULLER2016", "SETON2012", "GOLONKA", "MATTHEWS2016")
#run acros... |
ade7bcc5cbf1dc15f104b21afdaa215c34ea2c26 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/Devore7/examples/ex13.52.Rd.R | 15e6cbd23d531ba43472aa7911c24d07b96d190a | [] | 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 | 160 | r | ex13.52.Rd.R | library(Devore7)
### Name: ex13.52
### Title: R Data set: ex13.52
### Aliases: ex13.52
### Keywords: datasets
### ** Examples
data(ex13.52)
str(ex13.52)
|
f6e6538c708f4b71bad3d0e40ba38fd2262683a9 | 3f97fd801b7c8bdd69fb7f86373b7338b32e5d1a | /man/validate_naomi_population.Rd | 3cfb9857187b76606a31d3fc77a0d445902efa29 | [
"MIT"
] | permissive | kklot/naomi.utils | 083390022ed66194f7b93cf6daea68d3c74a650d | 2b14594b08191625a338173284976c39d6aa7606 | refs/heads/master | 2023-04-04T17:55:42.064764 | 2021-03-01T09:08:47 | 2021-03-01T09:08:47 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 614 | rd | validate_naomi_population.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils_population.R
\name{validate_naomi_population}
\alias{validate_naomi_population}
\title{Validate naomi population dataset}
\usage{
validate_naomi_population(population, areas, area_level)
}
\arguments{
\item{area_level}{area level(s) at ... |
355c6a75ee73ebb4d9c28699297d4c32776f2abb | b6fdf49a8a59a59e29b3ef3bd4288ec1ae30f764 | /math.R | afc5390ee335e2d2cd789a91bd90833715e0053e | [] | no_license | meenapandey500/R_Programming- | 879d1b7fd93aecd8da93bafc4805a813b6fc5de6 | b0ec5745c4cdccd745ccbcba8f8f0360018484f1 | refs/heads/main | 2023-03-25T03:21:02.679405 | 2021-03-19T09:42:41 | 2021-03-19T09:42:41 | 349,368,745 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 387 | r | math.R | a=as.numeric(readline("Enter Number a"))
cat("\n 1. round() \n2. ceiling() \n 3. floor \n 4. truncate\n")
ch=as.integer(readline("enter your choice"))
switch(ch,
cat("\n Value of a after decimal 2 digit :",round(a,digit=2)),
cat("\n ceil : ",ceiling(a)),
cat("\n floor : ",floor(a)),
c... |
1b0e3c963d7b982a8b007481b183bcaf66a08a96 | bd45db9efaa8770661ddb06a66ca2cfeab408a34 | /R/api-hc-hc_add_series.R | 56f4d7a4faf4c42ace8766cb78d01292868fac31 | [] | no_license | APKBridget/highcharter | a6c14524d937e731103f322cc71df261bf586c8f | 03e947d546a126c97051ed6db7ddd427914152ad | refs/heads/master | 2020-07-01T04:57:32.074899 | 2016-11-17T02:20:50 | 2016-11-17T02:20:50 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,070 | r | api-hc-hc_add_series.R | #' Adding and removing series from highchart objects
#'
#' @param hc A \code{highchart} \code{htmlwidget} object.
#' @param data An R object like numeric, list, ts, xts, etc.
#' @param ... Arguments defined in \url{http://api.highcharts.com/highcharts#chart}.
#' @examples
#'
#' highchart() %>%
#' hc_add_series(d... |
17d69f1bbda162a2bbdeabf28dac745af78153bc | f301db0962617354de8afa835e3de27c5bc6d51e | /man/flyhelp.Rd | c982bfa377f84685033b1822970f27d0c8a5f1b8 | [] | no_license | Dasonk/flydoc | 286abb4288694b719e4daa994fdf2caadd15f359 | 26a7a467bbfecfd44884df678fbd7139cd4f4afd | refs/heads/master | 2021-06-29T20:15:47.335683 | 2017-03-16T16:30:07 | 2017-03-16T16:30:07 | 6,071,319 | 3 | 1 | null | null | null | null | UTF-8 | R | false | false | 691 | rd | flyhelp.Rd | \name{flyhelp}
\alias{flyhelp}
\title{Show the documentation for a flydoc function}
\usage{
flyhelp(fun)
}
\arguments{
\item{fun}{The function to show the flydoc for}
}
\description{
This builds and shows the documentation for a function
that has been documented using flydoc
}
\examples{
myfun <- function(x, y)... |
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