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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ec0df17284d99dd0031b835b6bbe339d46f78d40 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/fam2r/examples/LRparamlink.Rd.R | 13ba317ada74ad866103db54abc75a1017004a1b | [] | 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 | 356 | r | LRparamlink.Rd.R | library(fam2r)
### Name: LRparamlink
### Title: Calculates likelihoods and likelihood ratios using 'paramlink'
### Aliases: LRparamlink
### ** Examples
data(adoption)
x = Familias2linkdat(adoption$pedigrees, adoption$datamatrix, adoption$loci)
result = LRparamlink(x, ref=2)
# Only marker 11 and 33
result33 = LRpara... |
e248bb1a6402a0091a9ce2f1c172577143cd90d5 | 5f16d226ba297a3a8886ead66ebf28bc74325e07 | /letraANum.R | 9d6811e0ce034be627e7f922b5411360574fe094 | [
"CC0-1.0"
] | permissive | datajules/UtilidadesR | 1dc51470d95e9a8af72f0e0a702e7e498c8f0093 | d5f5cfd587e6f20fd16089fe435ec32f9e72f9d6 | refs/heads/main | 2023-06-19T05:22:01.740843 | 2021-07-13T17:57:09 | 2021-07-13T17:57:09 | 385,690,783 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 799 | r | letraANum.R | # Función para convertir una letra a número para interpretar de mejor manera
# las columnas de exce.
library(tidyverse)
letranum <- function(letra){
x <- function(letra){
letra = str_to_upper(letra)
salida <- switch(letra,
'A' = 1,
'B' = 2,
'C' = 3,
'D' = 4,
'E' = 5,
'F' = 6,
'G' = 7,
'H' = 8,
... |
af39d0c8ef492b74feb1e2feda4a70a07a151ca1 | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/YPBP/R/ypbp.R | 33af657f471fc5589763fe2af5acf6de0fa59013 | [] | no_license | akhikolla/testpackages | 62ccaeed866e2194652b65e7360987b3b20df7e7 | 01259c3543febc89955ea5b79f3a08d3afe57e95 | refs/heads/master | 2023-02-18T03:50:28.288006 | 2021-01-18T13:23:32 | 2021-01-18T13:23:32 | 329,981,898 | 7 | 1 | null | null | null | null | UTF-8 | R | false | false | 10,355 | r | ypbp.R |
#---------------------------------------------
ypbp.mle <- function(status, Z, degree, tau, g, G,
baseline=c("hazard", "odds"), hessian, ...) {
n <- nrow(Z)
q <- ncol(Z)
baseline <- match.arg(baseline)
if(baseline=="hazard"){
M <- 1
}else{
M <- 2
}
hyper_parms = list(h1_ga... |
4f2327abf3dcd48cf0b509f2cc48eb04e9b6f46c | e7d40077078eae86b06770e95474d245b33472a1 | /man/degMerge.Rd | f34d442312894866940b848e2e58035cdbf2f67f | [
"MIT"
] | permissive | lpantano/DEGreport | 1f90ac81886da7b96c024dfc8dbfe4831cf20469 | 0e961bfc129aab8b70e50892cb017f6668002e1a | refs/heads/main | 2023-01-31T23:33:51.568775 | 2022-11-22T14:40:17 | 2022-11-22T14:40:17 | 17,710,312 | 20 | 14 | MIT | 2023-01-20T13:55:22 | 2014-03-13T13:06:49 | R | UTF-8 | R | false | true | 1,453 | rd | degMerge.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clustering.R
\name{degMerge}
\alias{degMerge}
\title{Integrate data comming from degPattern into one data object}
\usage{
degMerge(
matrix_list,
cluster_list,
metadata_list,
summarize = "group",
time = "time",
col = "condition",
... |
cafa48b04ed276421a154b5e8c875e1660b80a47 | 2a165938c9e860f88d58d5281589757e735e7a7a | /plot5.R | 4802bdd0bf87f8ce232a4cc7bee161e90e479abb | [] | no_license | stevenzchen/ExploratoryPollutantGraphs | 567f13b3608f6002a58d7bc3a341639af9c77862 | d9e6092e4a6b17e31ff6bfccb1d4baf932fdf5ee | refs/heads/master | 2021-01-12T04:54:51.479179 | 2017-01-03T03:57:15 | 2017-01-03T03:57:15 | 77,810,177 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 989 | r | plot5.R | # Generate plot5: How have motor vehicle emissions from PM2.5 changed in Baltimore
# from 1999 to 2008?
# Answer: Slight downward trend with low confidence
# Steven Chen
library(dplyr)
library(ggplot2)
baltimoreCounty <- "24510"
emissions <- readRDS("summarySCC_PM25.rds")
sources <- readRDS("Source_Classification_Co... |
38824d70c6b229d5484cf84c05d1e9df0c9d583a | 308d107fd0cfffb6f13b9101f77bb6ed2f3fe9ae | /03 - Population dynamics/00.3 - Functions_Elasticity_SLTRE.R | eefb5211c7674852fbadf7b1a4f5e2f6848c42aa | [] | no_license | MarcoAndrello/Stoch_Demogr_Comp_Arabis | 08a5a241c76550aed1e70fb2aecd2b56d4724fba | d327e434e3a7634f28f7efa4acc27de7e4f2f25d | refs/heads/master | 2020-08-26T18:22:08.247883 | 2020-02-18T10:23:11 | 2020-02-18T10:23:11 | 217,101,255 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,342 | r | 00.3 - Functions_Elasticity_SLTRE.R | # Functions to calculate the deterministic intrinsic growth rate and deterministic elasticities to lower-level vital rates
# They areused in the SLTRE
# There is a Main version and a Seed bank version
# Main version
calc.elast.vital.rates <- function(surv, growth, F0, F1, F2){
# Number of stages
k <- length(su... |
5faba7e24b560f5438fc9fb7d90bfad2cbb2ba80 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/HK80/examples/WGS84GEO_TO_HK80GEO.Rd.R | e7b81c7ad4464173c7ddf8b9e3f951ffaa1ad8e9 | [] | 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 | 488 | r | WGS84GEO_TO_HK80GEO.Rd.R | library(HK80)
### Name: WGS84GEO_TO_HK80GEO
### Title: Convert WGS84GEO coordinates to HK80GEO coordinates
### Aliases: WGS84GEO_TO_HK80GEO
### Keywords: WGS84GEO HK80GEO
### ** Examples
options(digits = 15)
WGS84GEO_TO_HK80GEO(22.322172084, 114.141187917)
#### $latitude
#### [1] 22.3236998617778
####
#### $long... |
0c00b4c255d3351bef53fc37e8d832caeb32e60f | 2d7a1cc54c6ffee066633479428368f496f10ae9 | /ui_chat.R | b681a54d47c006b4c5d556bffd23041e76403723 | [] | no_license | ed-lau/proturnyze | 1cd456256ddc23221ff1217f989fdccdc3f522e6 | 50d0e1ae11dddb9dfde12b7f8b6aeb53f6de2b30 | refs/heads/master | 2021-01-09T20:12:10.018344 | 2018-10-09T15:50:10 | 2018-10-09T15:50:10 | 62,418,218 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,836 | r | ui_chat.R | ###
### These are wrapper functions that separate parts of the UIs into separate pages for tidiness.
###
chat_page <- function(){
tabPanel("Help",
tagline(),
sidebarLayout(
sidebarPanel(
h3("Help and ... |
d40dad0b224672dc2d26d4cb30a781a3f7ea8dc8 | c064ecc411c2e7eed372b45d78875732ebf5e9c5 | /04 - Data Frames/27 - Importing Data into R.R | 5dcc2132a4f40b7247b0d49ca2c025505322f131 | [] | no_license | panchalashish4/R-Programming-A-Z | 3542078161a6eea51f0f61e49358a4c6abb63b97 | 61f3978cd7d1e2241265dc85cea768cdbc2bdeec | refs/heads/main | 2023-08-07T13:17:54.765000 | 2021-10-03T06:13:28 | 2021-10-03T06:13:28 | 408,997,386 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 291 | r | 27 - Importing Data into R.R | #Reading file
?read.csv()
#Method1: Select File Manually
stats <- read.csv(file.choose())
stats
#Method2: Set WD and Read Data
getwd() #To check current directory
setwd("C:/Users/Name/Desktop/R Programming") #To set working directory
rm(stats)
stats <- read.csv("P2-Demographic-Data.csv") |
724c5ea42f1f4d4c5ac519d014a094c054955943 | 5d4dcc088f0c711605e00e90920b9d21b4ffa5dd | /marketprofile.R | e893161fe5f6f26b727ac70fffd7dcd0c02d9e6c | [] | no_license | jes-moore/shinycharts | 78425d672f08a1b45d7a507284b8f3a632adc4b5 | ee9289c1913d31752ab495adebf86ea5977c3ac5 | refs/heads/master | 2021-05-29T06:49:11.502738 | 2015-09-24T02:22:10 | 2015-09-24T02:22:10 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,447 | r | marketprofile.R | marketprofile <- function(Ticker){
###############Market Profile#########################
stockdata<-read.csv(paste("http://chartapi.finance.yahoo.com/instrument/1.0/",Ticker,".AX/chartdata;type=quote;range=",5,"d/csv",sep = ""),
skip=22,
header = ... |
216c4c40509e07a332cf95423b9f28b2e6cf1f95 | 235979ce8f957b0ec258bfc9b9f90b64c15798b1 | /man/iWellPlot.Rd | 91dbef53dbc51f198e64197bc57711a6e282d244 | [] | no_license | cran/iScreen | d7843cf5bb6b0afcfa30420d10d825dee2136d39 | 859c3f95cd29ad819c39437a647f4615b826c910 | refs/heads/master | 2021-01-01T16:40:38.035847 | 2014-02-03T00:00:00 | 2014-02-03T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 480 | rd | iWellPlot.Rd | \name{iWellPlot}
\alias{iWellPlot}
\title{Plotting iWell}
\usage{
iWellPlot(object, xlab = "X", ylab = "Y", ...)
}
\arguments{
\item{object}{A iScreen object.}
\item{xlab}{Default is "X".}
\item{ylab}{Default is "Y".}
\item{...}{Arguments to be passed to methods. See
\code{\link{plot}} and \code{\link{pa... |
7cbdb9d721f55e4ed5bad53c1cf6b279de403680 | 6a28ba69be875841ddc9e71ca6af5956110efcb2 | /Mathematical_Statistics_And_Data_Analysis_by_John_A_Rice/CH8/EX8.4.D/Ex_8_4_D.R | 92815540c0bb5274063e127e7867c783cfa5c061 | [] | permissive | FOSSEE/R_TBC_Uploads | 1ea929010b46babb1842b3efe0ed34be0deea3c0 | 8ab94daf80307aee399c246682cb79ccf6e9c282 | refs/heads/master | 2023-04-15T04:36:13.331525 | 2023-03-15T18:39:42 | 2023-03-15T18:39:42 | 212,745,783 | 0 | 3 | MIT | 2019-10-04T06:57:33 | 2019-10-04T05:57:19 | null | UTF-8 | R | false | false | 169 | r | Ex_8_4_D.R | #Page 119
library(Ryacas)
f = function(x,a) x*(1 + a*x)/2
x = yac_symbol("x")
a = yac_symbol("a")
miu = integrate(f(x,a),"x",-1,1)
print(simplify(miu))
|
4ff5a234f24e203d7615aacf477c4e2bc1ada2ec | 0ddeb15558a11d46e79f32adeea383ed2bb30389 | /Part3/section5.R | 2851a97c2759e375c9b66a08bd792b9166cb0c07 | [] | no_license | HyungcheolSon/R | b79150b0b15cc2fb52ef31c2995b2a51a07debf3 | e22f85ab75514eb7d815fdaf1c13208cd57d5257 | refs/heads/master | 2020-06-02T22:34:16.342852 | 2019-06-14T02:12:17 | 2019-06-14T02:12:17 | 189,161,629 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 780 | r | section5.R | <<<<<<< HEAD
var1 <- "aaa"
var2 <- 111
var3 <- Sys.Date()
var4 <- c("a","b","c")
var1
var2
var3
var4
111 -> var5 -> var6
String1 <-"So Easy R Programming"
String1
String2 <- "I'm Hyungcheol Son"
String2
comp <-c(1,"2")
comp
class(comp)
num1<-1
num2<-2
num1+num2
seq1<-1:5
seq1
seq2<-1:11
seq2
String2
rm(String2)
String... |
8fc528161aad18d8784c2ef29fcd65cef3599eae | 768550e0018f0f6db82d99073736bb7511972eeb | /man/get_bref_all_nba_teams.Rd | 2649c4af30be7471b23bd07074360ae5db7ce59a | [] | no_license | chadmillard/nbastatR | 74964e3af974edec814d9767ba1636ff6d65553c | 3ab473beeb7564dc21d59036bca4df87b6f2ce89 | refs/heads/master | 2020-03-26T12:25:44.419875 | 2018-07-29T17:43:49 | 2018-07-29T17:43:49 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 607 | rd | get_bref_all_nba_teams.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bref.R
\name{get_bref_all_nba_teams}
\alias{get_bref_all_nba_teams}
\title{All NBA teams}
\usage{
get_bref_all_nba_teams(only_nba = T, return_message = T)
}
\arguments{
\item{only_nba}{if `TRUE` returns only NBA all NBA teams}
\item{return_m... |
4f6cfa88cf5607e3d42f7bd9fb85694ac03ba094 | 9e4df408b72687493cc23144408868a975971f68 | /SMS_r_prog/flsms/flindex.sms.r | 4fc3d9e5908a24d203777e13ff7f6c6e7b8418aa | [
"MIT"
] | permissive | ices-eg/wg_WGSAM | 7402ed21ae3e4a5437da2a6edf98125d0d0e47a9 | 54181317b0aa2cae2b4815c6d520ece6b3a9f177 | refs/heads/master | 2023-05-12T01:38:30.580056 | 2023-05-04T15:42:28 | 2023-05-04T15:42:28 | 111,518,540 | 7 | 0 | null | null | null | null | UTF-8 | R | false | false | 9,058 | r | flindex.sms.r |
setClass("FLIndex.SMS",
contains="FLIndex",
representation(
range.SMS="vector"
) ,
prototype=prototype(range.SMS=list(season=1, power.age=-1, q.age=0,
var.age.group=as.vector(0,mode="list"),minCV=0.3))
)
FLIndex.SMS <- function(name=character(0), desc=character(0), distribution=cha... |
fdb971d72716f7cc499a3bbe90ea69d19a0dce71 | 92895544621673dc09df46643ffcfe5158de5106 | /R/rbing.matrix.gibbs.R | a804c06c59f69584f686d845829ffa3e996e1b85 | [] | no_license | pdhoff/rstiefel | 39f6a1541aa424a8964bd4edf0382e9a343f7b42 | c19d696e357365f3dc814400fb56e7b254d11983 | refs/heads/master | 2021-06-18T23:41:10.289312 | 2021-06-15T13:59:20 | 2021-06-15T13:59:20 | 94,270,392 | 1 | 2 | null | null | null | null | UTF-8 | R | false | false | 2,278 | r | rbing.matrix.gibbs.R | #' Gibbs Sampling for the Matrix-variate Bingham Distribution
#'
#' Simulate a random orthonormal matrix from the Bingham distribution using
#' Gibbs sampling.
#'
#'
#' @param A a symmetric matrix.
#' @param B a diagonal matrix with decreasing entries.
#' @param X the current value of the random orthonormal matrix.
... |
bee6289441d52ec5abacc2e05dc1071b2c4318a5 | 0815d30d5e9a9b13466a728b4795e63bf7a81c25 | /Scripts/4 - Trait GWAS colocalization figure.R | 2efdb719b500a1f7b7a16504f39c45ed55728976 | [] | no_license | ntduc11/Sunflower-GWAS-v2 | 5e82506e88a39934f22a8a08b9a03892fb8a36af | 14bb4d4ef23c25651b1a462d67f89b77d1155910 | refs/heads/master | 2022-12-01T06:39:39.065583 | 2020-08-13T13:09:28 | 2020-08-13T13:09:28 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,374 | r | 4 - Trait GWAS colocalization figure.R | library(gridExtra)
library(ggpubr)
library(cowplot)
library(wesanderson)
#### read in preferences
prefs<-read.table("Scripts/### Preferences ###",header=F,sep="=",skip=1)
SNPset<-as.character(prefs[2,2])
pheno.name<-as.character(prefs[1,2])
multcomp<-as.numeric(as.character(prefs[3,2]))
##########
colors<-c("#1... |
451d2ba4ae509c2fa8cb72e3a3665bcfd7282edf | 502905b70f6c559f81539c72f5963527a6c287c5 | /R/coltable.R | f18b84aae10ce0ee2eeb9ddfb9c88e8de0889c8e | [] | no_license | aswansyahputra/SensoMineR | b524b84fd211a49d57a0ccb6735f6c8ae063783e | 108ba9af4abec264d69285f021e52c523dde6c7f | refs/heads/master | 2020-04-17T22:44:08.643840 | 2019-01-22T14:35:17 | 2019-01-22T14:35:17 | 167,006,296 | 0 | 0 | null | 2019-01-22T14:16:52 | 2019-01-22T14:16:51 | null | UTF-8 | R | false | false | 12,387 | r | coltable.R | #' Color the cells of a data frame according to 4 threshold levels
#'
#'
#' Return a colored display of a data frame according to 4 threshold levels.
#'
#' This function is very useful especially when there are a lot of values to
#' check.
#'
#' @param matrice a data frame (or a matrix) with only quantitative varia... |
1de97b0cedcb75ff9a985f5fd6f4521f4ad32f08 | 359734ced390a49899f91dc6b1e7ac27d724f3da | /scripts/Mapping_example.R | c938ea9213fcffc793858874b9bdfc5ced6b68bf | [] | no_license | QFCatMSU/R-Mapping-Material | 5997f3c8a74167e76fc401cc18c01ac3ba2989a2 | 7579d56ac35e09e6a0feb9b6152e49a30c722bde | refs/heads/master | 2022-04-19T11:20:24.548009 | 2020-04-21T18:43:25 | 2020-04-21T18:43:25 | 254,618,906 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,225 | r | Mapping_example.R | {
# execute the lines of code from reference.r
source(file="scripts/reference.R");
# read in CSV files
data <- read.csv(file="data/TempLogger_Coordinates.csv")
}
# this code makes a map.... but mapview includes
# toggles, multiple layers, and clickable attribute tables,
# all of which leaflet can't do w... |
8241a9481d8c76ad111a16321ca796e1bb3a5a69 | 960f4ee096f3179e51ea185d4eb9f4f48e5778f7 | /Pokemon Final.R | 77a2b52de72f7dbed66337dd71d777c65b2cbd89 | [] | no_license | tylerjnelson8/PokemonClassification_April2020 | 3adfa40a7e5858bb7a4b529342b11636c718ac5b | 0d52af0db4dc8c402db6a9c1dd4b78ace850f626 | refs/heads/master | 2022-06-09T00:34:26.288159 | 2020-05-04T23:49:59 | 2020-05-04T23:49:59 | 261,076,762 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,123 | r | Pokemon Final.R | #Using Multi-class and One-vs-Rest SVMs to Classify Pokemon by their Primary Type
#by: Tyler Nelson
rm(list = ls())
library(EBImage) #used for image processing
library(OpenImageR) #used for image processing
library(reshape2) #used for data cleaning
library(ggplot2) #used for data visualization
library(dplyr)... |
90c7b01bb0c3f4768280c5def6b683aa7bdbecbb | 4fcf313905a8be596449cf2d78a8f2f35abdc2ae | /tests/generateRd.R | 32f57e0c2bfa2c5d83de04c73867db25f5ae9290 | [] | no_license | wangdi2014/gfplots | 0ceb7dbc0c9fcaf3d31344c2b6ee03cf5eb4fa21 | 2e9bbe64f6bf4b743a4387c326c00e7e08d53998 | refs/heads/master | 2020-06-07T05:02:38.624900 | 2018-06-14T14:00:24 | 2018-06-14T14:00:24 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 33 | r | generateRd.R |
library(roxygen2)
roxygenise()
|
24bede4045c6f0de67d0ac2ae782002bf14b0253 | b15b9944047fc333f2068d0883d511d295da7ad9 | /R/methods.R | f4274709d440098675a7fcd6fd8d6902e6dc7656 | [] | no_license | cran/outForest | 12b9905b9692de1ea9669f153f4d630b7cc225e8 | 8dd25dbef51a4549782cea357e0776ea9e64d7c1 | refs/heads/master | 2023-05-25T16:11:19.136495 | 2023-05-21T17:50:02 | 2023-05-21T17:50:02 | 236,635,053 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,050 | r | methods.R | #' Prints outForest
#'
#' Print method for an object of class "outForest".
#'
#' @param x A on object of class "outForest".
#' @param ... Further arguments passed from other methods.
#' @returns Invisibly, the input is returned.
#' @export
#' @examples
#' x <- outForest(iris)
#' x
print.outForest <- function... |
349b0f98ae0c7617226f1636799a080b6e735054 | ea9fbb9669d73bb53b944b33914c1ddbbe1e7cb3 | /script_diversity_indices.R | 7a16b3f7fc3a2dd34ff9382d2c1dbf647c7b7c74 | [] | no_license | mizubuti/R_code | 33ebdbbc85e2f282cee2102e2568928f8087652c | 05ad1e5f7124d097ac6969e768bd8c55a0d562d3 | refs/heads/master | 2021-01-02T09:08:03.058788 | 2016-12-30T16:52:55 | 2016-12-30T16:52:55 | 34,257,584 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,434 | r | script_diversity_indices.R | # ==========================================================
# scripts for diversity indices
# ======================================= E. M. 17/09/2016 =
# this script uses "vegan" and "vegetarian" package
# organizacao dos dados
# prepare o conjunto de dados com cada populacao em uma linha.
# nas colunas insira as... |
b27a1e50a15009c7e01ff9cac41cd3c775e6882b | 4974a00cd842967834be1c62b85c1dbe08b788fd | /man/getParameterSet.Rd | 740971cb3c32d32a95e28183e252417e38a1b62f | [] | no_license | cran/plethem | afcdc38f32a0bfc4f55eac7b8f4a73b261bfb58e | fbbd513ab824c0d378b130a25970dcdfca2dfd9a | refs/heads/master | 2021-06-27T00:54:23.595226 | 2020-11-04T14:50:07 | 2020-11-04T14:50:07 | 163,861,169 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 440 | rd | getParameterSet.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pbpkUtils.R
\name{getParameterSet}
\alias{getParameterSet}
\title{Get the values for parameters in a given set}
\usage{
getParameterSet(set_type = "physio", id = 1)
}
\arguments{
\item{set_type}{Either "physio","chem"or "expo"}
\i... |
a8fd123026a5a1af030a026a8c0ba59924f1a860 | 076291ef89acc7c93bd777dfe280fbe9d401174c | /switching_ise.R | c13a9b79a932855c21353cb42d4c0d900e8c47d3 | [] | no_license | vkatkade/R-case | c87f8f7d1c0bbd23cc0e7a74cc608af1d783725c | fc47ffb04fb744cea404b00dd80e5dbc289d2b9b | refs/heads/master | 2021-01-17T11:57:49.453071 | 2013-09-01T05:39:37 | 2013-09-01T05:39:37 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,942 | r | switching_ise.R | # Script to determine common customers and their respective bookings amongst Switching and ISE customers
# Copyright (c) Vaibhav Katkade - August 2013
setwd("/Users/vkatkade/Desktop")
library(plyr)
cise <- read.csv("CISE.csv")
c6k <- read.csv("fyc6k.csv")
# Remove all the adjustments and disti stock which have negati... |
ee9f3ba40d089e2b1928d273408c497a889591da | b545da725d70f13c023f8b34660b46536a27288d | /older_files/future_processing.R | 9a5d70a871d78710d2e42c4b6c0f2a1b6767f321 | [] | no_license | baeolophus/ou-grassland-bird-survey | b64849e5b7c3bf63e1854da5454d3295a4df0709 | 5aa9523a3d09d107a7d92140de7fa8ec62fe411a | refs/heads/master | 2020-04-13T05:23:20.801879 | 2019-05-13T18:59:49 | 2019-05-13T18:59:49 | 68,133,712 | 0 | 1 | null | 2016-09-29T21:01:03 | 2016-09-13T18:01:07 | R | UTF-8 | R | false | false | 2,284 | r | future_processing.R | ##################################
#process the future bioclim layers the same way as bioclim (though use the ok_mask_resample to make sure I don't need to crop again later)
#import bioclim layers
setwd("/data/grassland_ensemble")
library(raster)
library(rgdal)
#create temporary raster files on large drive because the... |
935204ee5966f11aec428d39e04aae849c0aa4a0 | b061608d5d95a8b1c45a0f147db64fff399b9bb9 | /Generate OD Matrix/Generate-OD-Matrix-undirected.R | a8a087cfe74db2246c696fcf7e95e3ed02ed45d3 | [] | no_license | ecoinformaticalab/city-networks | 30556e9f28c6db06a8b7028de0347500677dda72 | 6063a281784ac0d605e93ebf51003199d197741b | refs/heads/master | 2020-04-24T04:08:33.677690 | 2019-02-20T15:07:59 | 2019-02-20T15:07:59 | 171,692,867 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,101 | r | Generate-OD-Matrix-undirected.R | #Generar matriz HW
library(dplyr)
library(rstudioapi)
#Firstly we obtain the path where "Generate-OD-matrix-undirected.R" is located
path<-print(rstudioapi::getActiveDocumentContext()$path)
folder<-gsub("Generate-OD-Matrix-undirected.R","",path)
#The file where the trajectories list is allocated is called "list.cs... |
196991433242b8d11ce6e261fe3b5a5623d0db3f | d3ed30ed9dc4d9f7b6f1184c81bac390927037ff | /sinha2017/brc_post_proc.r | 5eb7e94b985c5e2d0d618eb1cb7cbd1a518d1a44 | [] | no_license | mikemc/mc_datasets_backup | 3af6bc916ba8a682c730e38eb5a4aca9248d416a | 50fc997d8bd8737ea9d87fad19222b22746a0d8a | refs/heads/master | 2020-03-20T10:06:02.493285 | 2018-10-06T21:03:29 | 2018-10-06T21:03:29 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,188 | r | brc_post_proc.r | # Load packages
library(phyloseq)
library(dada2); packageVersion("dada2")
## Paths
# Path for raw sequencing data and pipeline output
data.path <- "~/active_research/metagenomics_calibration/mbqc/data"
# Path for silva training data
silva.path <- '~/data/silva/dada2_format'
#### Get the sample data for incorporation ... |
e57992569ab2f1087bea9ade4c80600d0013862f | e784dc9d52588bc6c00fa18fab014f6cf3fe73b7 | /R-Finance-Programming/ch03_graph/30_substitute.R | 072e194ff5b6505eaf102bff80765d27080f966e | [] | no_license | Fintecuriosity11/Finance | 3e073e4719d63f741e9b71d29a97598fa73d565d | b80879ece1408d239991d1bb13306cc91de53368 | refs/heads/master | 2021-02-20T12:59:51.559033 | 2020-08-08T16:21:49 | 2020-08-08T16:21:49 | 245,337,007 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,339 | r | 30_substitute.R | ##########################################################################################################################################
#(주의) -> 순차적으로 코드를 실행하는 것을 권함!
#에러 발생 시 github Finance/R-Finance-Programming 경로에 issue를 남기면 확인
##################################################################################... |
cfe2b9e8206e1bca87f75bc8a69c6ee64d71f5c8 | cf0c1117b47a005f91a1533046117e6ef69b9914 | /Sentiment Analysis.R | bb2e60fd2ffafd29fd9a5d94ed729bc6bb9a1e64 | [] | no_license | RCrvro/Social-Media-Analytics-Project | 5bc46326f75feef8c76ba2dba1038561ad71028b | 19d9ecff16007a42090ad15965eba42f027aa0d5 | refs/heads/master | 2022-11-08T06:55:17.622093 | 2020-06-22T17:58:44 | 2020-06-22T17:58:44 | 269,715,767 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 863 | r | Sentiment Analysis.R | ##Lexicon-based Sentiment Analysis
#Removed duplicates for each community
#Lemmatization with POS tagging
library(tidytext)
library(syuzhet)
library(dplyr)
library(ggplot2)
library(fmsb)
#Load database
db <- read.csv("/Users/riccardocervero/Desktop/db.csv")
#Analyse total database
result <- get_nrc_sentiment(as.cha... |
9d2f7992eb31579f90061f9846320a068a694e7f | beb174618e3ba35aab378218151077b32dcb624b | /cachematrix.R | 7badcaf99eff5dac0194df5b0434e87aea8cc411 | [] | no_license | mattiasherrera/ProgrammingAssignment2 | d735384e7df4ec7bddad6c5be5de447aa3e9ba01 | 808d7c9853109515cc92942d73c03dce2c458e8b | refs/heads/master | 2021-01-17T08:50:57.795902 | 2015-06-20T05:09:47 | 2015-06-20T05:09:47 | 37,702,365 | 0 | 0 | null | 2015-06-19T04:56:09 | 2015-06-19T04:56:07 | null | UTF-8 | R | false | false | 2,267 | r | cachematrix.R | ##This a function that creates a matrix, sets a matrix, gets the inverse or sets
##the inverse
makeCacheMatrix <- function(x = matrix()) {
##Initialize the Inverse of the matrix inverse_x to NULL
inverse_x <<- NULL
##function to set a new matrix y
setmatrix <- function(y){
... |
54d40824a55ff61a850c0b67438f44768e7f0d22 | f1971a5cbf1829ce6fab9f5144db008d8d9a23e1 | /packrat/lib/x86_64-pc-linux-gnu/3.2.5/pool/tests/testthat/test-release.R | abbf37a0e55389fc00890e823cafb46471620fcc | [] | no_license | harryprince/seamonster | cc334c87fda44d1c87a0436139d34dab310acec6 | ddfd738999cd302c71a11aad20b3af2f4538624f | refs/heads/master | 2021-01-12T03:44:33.452985 | 2016-12-22T19:17:01 | 2016-12-22T19:17:01 | 78,260,652 | 1 | 0 | null | 2017-01-07T05:30:42 | 2017-01-07T05:30:42 | null | UTF-8 | R | false | false | 1,336 | r | test-release.R | source("utils.R")
context("Pool's release method")
describe("release", {
pool <- poolCreate(MockPooledObj$new,
minSize = 1, maxSize = 3, idleTimeout = 1000)
it("throws if object was already released", {
checkCounts(pool, free = 1, taken = 0)
obj <- poolCheckout(pool)
poolReturn(obj)
expect_e... |
e8ba8f96e53fca6dda451cb9d1226affc49502b0 | a64f5b231c65e042ae359ea3088e130bfae5dae8 | /preregCreator.R | 812d83b6a0bf6d1f2d8f58923f943e847bd8efa0 | [
"MIT"
] | permissive | johalgermissen/mapMEEG | 5d378ed0a9a131adb6592839f9b7b37c630d0cfb | fdd034c8b099dd728dae66352ae3b2055edea670 | refs/heads/master | 2022-11-07T10:31:23.919454 | 2020-06-19T11:03:53 | 2020-06-19T11:03:53 | 270,663,362 | 1 | 4 | MIT | 2020-06-20T07:18:53 | 2020-06-08T12:38:34 | R | UTF-8 | R | false | false | 1,521 | r | preregCreator.R | library(shiny)
library(glue)
source("templates.R")
ui<- fluidPage(
fluidRow(
column(12,
div(id = "header", align = "center",
h1(icon("brain"), "M/EEG pre-registration template creator", icon("brain")),
p("__________________________________"),
p("This app helps you create more struc... |
c4e294904efb2707402f72592ed81e2e5750df80 | 154553c5d637755a8aebb29b681480714ad4c819 | /R/draw_names.R | 05da7b4fe3e0a7e68c0d8683bddbddb42d117fbf | [] | no_license | amirbenmahjoub/Package_DM | fb42cfc1e66c57af177e1e400dad0c09a91ee914 | 3b9749e80894e57160ab1dced41c01312534958a | refs/heads/master | 2021-05-08T08:31:11.217927 | 2017-11-24T15:36:32 | 2017-11-24T15:36:32 | 107,041,020 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 564 | r | draw_names.R | #' Plot the evolution of names occurences for different names
#'
#' @param names names you want to observe occurences data
#' @import dplyr tidyr ggplot2 prenoms
#' @return graph.
#' @export
#'
#' @examples
#' \dontrun{
#'
#' draw_names(c("name1","name2",...))
#'
#' }
draw_names <- function(names){
assert_tha... |
1145d4850c9eed30e47aacd8c14421fd25be657d | 15d7fe33eeb26d6824d2199f8bfc4e52c2f647c1 | /carpentry/002_dplyr_simple_joins.R | 9fc64e60134f16b46926cc4829c8f91010ab6ddc | [] | no_license | jalapic/learnR | 3a5a193295eb96a5aa53ff48b1cce0b6aa0e15d8 | 70ff52dc961facff363bf10ed667d3329dc6c81f | refs/heads/master | 2021-01-21T03:24:47.767208 | 2018-10-31T17:45:45 | 2018-10-31T17:45:45 | 101,895,479 | 21 | 10 | null | null | null | null | UTF-8 | R | false | false | 2,921 | r | 002_dplyr_simple_joins.R | ### dplyr joins basics
library(tidyverse)
## A common issue in data analysis is when you have two or more files that you
## need to join together in some way.
# this might be two dataframes of same length where you simply join
# this might be unequal lengths of two dataframes
# you may want to join bas... |
b08327a3cf5beec40259c4e3954799047dff2b53 | e55ffb2edab5f9658f23c46a23b84c78348b99eb | /r-ws/foundamental-data-transforming-labels.R | 42a7c4eaee131b7d91e14b99bb8d9c9dbe3d3006 | [] | no_license | un-knower/hadoop-ws | 6689dd20fd8818f18cfef7c7aae329017a01b8a9 | 913bbe328a6b2c9c79588f278ed906138d0341eb | refs/heads/master | 2020-03-17T23:15:21.854515 | 2015-04-25T08:09:03 | 2015-04-25T08:09:03 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,828 | r | foundamental-data-transforming-labels.R | # -----------------------------------------------------------------------------
# 数据变换
# 行号信息
# 标签
# -----------------------------------------------------------------------------
# 将行号信息变为一列 (为了将来melt!)
df <- data.frame(time = 1:10,
a = cumsum(rnorm(10)),
b = cumsum(rnorm(10)),
... |
a1c2435f57932f2087505f2c2adf5df58730b749 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/partialAR/examples/which.hypothesis.partest.Rd.R | 25f743ed32a7586c40777238614e6016ecff1606 | [] | 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 | 693 | r | which.hypothesis.partest.Rd.R | library(partialAR)
### Name: which.hypothesis.partest
### Title: Returns the preferred hypothesis when testing for partial
### autoregression
### Aliases: which.hypothesis.partest
### Keywords: ts models
### ** Examples
set.seed(1)
which.hypothesis.partest(test.par(rpar(1000, 0, 1, 0))) # -> "AR1"
which.hypothes... |
483c3639dad780f50582315990f5bc29248325f3 | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /cran/paws.analytics/man/quicksight_update_group.Rd | fd026664671b79919ffc71f01b8913b1559edf43 | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | true | 901 | rd | quicksight_update_group.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/quicksight_operations.R
\name{quicksight_update_group}
\alias{quicksight_update_group}
\title{Changes a group description}
\usage{
quicksight_update_group(GroupName, Description = NULL, AwsAccountId, Namespace)
}
\arguments{
\item{GroupName}{... |
99197e82b3efbb88d06396627a28002d995f80f1 | f61cea74c0ef7a4ae4e0812fcde5bed7bd2772ea | /ui.R | 151d1868cdeea6ca7dae088dccf87356e9d09776 | [] | no_license | jackytksoon/Shiny-Application-and-Reproducible-Pitch | c9038b5bef6fc6a408dd4a86c7c61dee3dc386d7 | dabe3245fdd35049d1ed3b6cf03f51390123acf8 | refs/heads/master | 2021-01-01T05:15:35.953455 | 2016-04-20T03:40:57 | 2016-04-20T03:40:57 | 56,646,248 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,371 | r | ui.R | library(shiny)
shinyUI(fluidPage(
titlePanel("Search Hospitals Name by Rank, State and Outcome"),
sidebarLayout(
sidebarPanel(
helpText("Select the state, outcome and rank you wish to check"),
selectInput("State", "State", c("AK", "AL", "AR", "AZ", "CA", "CO", "CT",
... |
93ca244783ee0cbe50c8138601a4f8d6a7b5f675 | ee4f2c2d6fceba9422623dea19773ae4c1560209 | /test_lib.R | 82221cf401cf4d3999109f365b2c7162b0751898 | [
"MIT"
] | permissive | granek/crne_cna1crz1_rnaseq | e51ec4e42450873b5abbbb02eaa12b9ae80b2cfb | 361abf7f082c52b8dc7bc9ab39089de2ce0c7ec3 | refs/heads/master | 2021-01-18T15:56:30.782871 | 2017-02-13T22:08:47 | 2017-02-13T22:08:47 | 62,157,192 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 641 | r | test_lib.R | if (interactive()){
basedir<<-file.path(Sys.getenv("CNA"),"rstudio")
} else {
basedir<<-"."
}
##================================================================================
outdir=file.path(basedir,"results")
annotdir = file.path(basedir,"info")
suppressPackageStartupMessages(library("DESeq2",lib.loc="/Use... |
c190d62799241317bb212aa9621d13581774aa6f | 20fb140c414c9d20b12643f074f336f6d22d1432 | /man/NISTkgPerCubMeterTOpoundPerCubFt.Rd | ba4d606dbfb432fe9b7c2a06f9950a3c9b73c2b6 | [] | no_license | cran/NISTunits | cb9dda97bafb8a1a6a198f41016eb36a30dda046 | 4a4f4fa5b39546f5af5dd123c09377d3053d27cf | refs/heads/master | 2021-03-13T00:01:12.221467 | 2016-08-11T13:47:23 | 2016-08-11T13:47:23 | 27,615,133 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 928 | rd | NISTkgPerCubMeterTOpoundPerCubFt.Rd | \name{NISTkgPerCubMeterTOpoundPerCubFt}
\alias{NISTkgPerCubMeterTOpoundPerCubFt}
\title{Convert kilogram per cubic meter to pound per cubic foot }
\usage{NISTkgPerCubMeterTOpoundPerCubFt(kgPerCubMeter)}
\description{\code{NISTkgPerCubMeterTOpoundPerCubFt} converts from kilogram per cubic meter (kg/m3) to pound per cub... |
40fd6c0e0f4e304c4d680f4f2b696e9c10488cef | 0d7f82ba1c9293177e67f2db06d07628b46d77a6 | /R/utils-vector.R | 3db615984ff2c46a89401a4e25138c1f4929d9a2 | [
"MIT"
] | permissive | rcodo/coro | 97430cbc30233f2b696b125535e3efe8695c525a | 015c6252a05ce6cb1160accbc38085b82c8a8466 | refs/heads/main | 2023-01-31T01:51:40.163190 | 2020-12-17T21:00:29 | 2020-12-17T21:00:29 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,076 | r | utils-vector.R |
vec_types <- c(
"logical",
"integer",
"double",
"complex",
"character",
"raw",
"list"
)
as_vector_fn <- function(type) {
if (!type %in% vec_types) {
abort("`type` must be a vector type")
}
switch(type,
logical = as.logical,
integer = as.integer,
double = as.double,
complex = as.... |
6724e8d2767cde3406f7f61945ee46fc930a7606 | 7bf239bf9446ac3073d0ebb6af4a2f3b2cb47af6 | /Lab3/Assignment 3/Assignment 3.R | 6bf42c71601ad40f00b6af93b21b12ac23dd0219 | [] | no_license | chreduards/TDDE01 | 9346b9dba73dc99d9c92c8b52aa201e09d97b4b1 | df1920930ac52c77b82b95b585de2175ddfc040e | refs/heads/master | 2020-04-24T02:31:58.720021 | 2019-02-21T10:25:05 | 2019-02-21T10:25:05 | 171,640,297 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,211 | r | Assignment 3.R | #### Import and divide data ####
setwd("C:/Users/Christoffer Eduards/OneDrive/R/Lab2/Assignment 1")
library(neuralnet)
set.seed(1234567890)
Var <- runif(50, 0, 10)
trva <- data.frame(Var, Sin = sin(Var))
tr <- trva[1:25, ] #Training
va <- trva[26:50, ] #Validation
#### Main ####
#Randomly generating the initia... |
ff389207c87993a6622e1b6caf37bf7119912b02 | f4a38ecb46a7721ada59c35cb5f573cbb901bee5 | /man/add_p.adjust.Rd | b6570f65e53a41754fb287bd34852f59458a9c75 | [] | no_license | biodatacore/biodatacoreMTM | c080e11c2e5440c9fe9d6c9737df543dd69b40dd | bb2541c5132fdb96d79849a50890a9c2c9101913 | refs/heads/master | 2021-05-14T18:08:26.872845 | 2018-01-02T22:50:34 | 2018-01-02T22:50:34 | 114,794,630 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,031 | rd | add_p.adjust.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/add.R
\name{add_p.adjust}
\alias{add_p.adjust}
\alias{add_bonf_pv}
\alias{add_fdr_pv}
\title{Adds columns of adjusted p-values}
\usage{
add_p.adjust(data, method = stats::p.adjust.methods, p_value = "p.value",
var = NULL)
add_bonf_pv(data,... |
8942f17de972d757c6135e251ac04f7cb9fa5cc3 | 994dc87cc09e2fa8a470f9920492d4a6527465e8 | /test_people/People_neuronet.r | 6d8e695b6ccecab96939e7274ddd9609a96ac1e4 | [] | no_license | Basnor/At_risk_students_analizer | 2b04cd97ddbf5bf4e5cd041ca694df893b726770 | 51c4617bb3d1927e2d64241953895005563682b5 | refs/heads/master | 2023-01-09T17:53:20.286163 | 2020-11-03T06:50:50 | 2020-11-03T06:50:50 | 281,601,434 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,218 | r | People_neuronet.r |
## -----ЧТЕНИЕ-ВЫБОРКИ-ДЛЯ-ОБУЧЕНИЯ--------------------------------------
PeopleTrain <-read.csv(file = "PeopleTrain.csv", header = TRUE, sep = ";", dec = ",")
# нормализации данных
PeopTrain <- list(class = PeopleTrain$Class, data = PeopleTrain[,c(2:13)])
rm(PeopleTrain)
Y_train = PeopTrain$class
X_train = PeopTrain... |
ea8488a75d48de5da714d48fd62e8bc072f84d0c | eb3cccfd5a08362c0933688b6afc481d29db0100 | /milk_customer_preference.R | ee715c5de0d6309490c4eecbc1d0a14b9a0c5cc0 | [] | no_license | xjhee/Dairy-Farm-International-Holdings-Ltd.-customer-preference-data-analysis | 534f62143732dda76839dacd4146dc227b248c15 | 5796de9ea8886abe523c1c02e2003b825e6554b1 | refs/heads/master | 2020-08-27T07:24:40.467010 | 2019-10-24T12:21:11 | 2019-10-24T12:21:11 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,124 | r | milk_customer_preference.R | #this study investigates consumer preference in different milk attributes based on eight factors
#x1: Taste
#x2: Fact content
#x3: High quality certification
#x4: Origin
#x5: Price
#x6: Organic certification
#gender; level of education
library(psych)
library(reshape2)
library(ggplot2)
library(forecast)
#load the milk ... |
32aa64f374d0870a12d80b329ffb500844b874d1 | 6fd02f84552ba4298d8009cbee053f72d189db0b | /ui.R | 420b55745dddc9d6a5402f815d040a4b68b715c5 | [] | no_license | uc-bd2k/webgimm | 0573ce671ed611eda1d4b686975068b3157cb085 | d6116766ab14e3f04ab465096ef2f7eb5858edcb | refs/heads/master | 2020-03-19T08:20:28.107228 | 2018-10-17T13:38:11 | 2018-10-17T13:38:11 | 136,196,960 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,030 | r | ui.R | library(shinyjs)
library(shinyBS)
library(DT)
library(morpheus)
library(shinycssloaders)
source("helpers.R")
shinyUI(fluidPage(style = "border-color:#848482",
useShinyjs(),
# Application title
navbarPage(strong(em("Webgimm Server",style = "color:white")), inverse = TRUE, position = "fixed-top"
... |
12dabd157f4668461d42ae64e901f60cd5a30f5d | 655ee959878fc9fa6f0ffdd7fb956f38936c2072 | /symbolicR/man/create.polynomial.of.random.variable.Rd | 7c33daad9392eee4c01ad5b7f2a1b70617f79089 | [] | no_license | isabella232/symbolicR | 29b1b28334f8889846156d8fd1effdbec6164e6d | 001707e9a380de37a8f7fe3d2a463cf047733109 | refs/heads/master | 2023-03-16T00:08:39.874076 | 2017-12-13T10:00:47 | 2017-12-13T10:00:47 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 615 | rd | create.polynomial.of.random.variable.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/00symbolic.002monomial.R
\name{create.polynomial.of.random.variable}
\alias{create.polynomial.of.random.variable}
\title{create.polynomial.of.random.variable}
\usage{
create.polynomial.of.random.variable(e)
}
\arguments{
\item{e}{expression}
... |
f6416a48ce9724f071b9474bf7d532355e609bd2 | 967867d8b9dc76f7650de576b858c2ed084ba655 | /ChIPseq_scripts/TF_polII_topGO.R | b759cf95a3753194711c31d9445d554ca1a73ee1 | [] | no_license | lakhanp1/omics_utils | 5f5f2ae9b840ef15fc0cd1c26325d9a2dbdb8dc5 | 0485f3d659225b127f9c3e5bc53ab3d84c42609b | refs/heads/main | 2023-08-31T12:29:03.308801 | 2023-08-30T20:40:42 | 2023-08-30T20:40:42 | 160,330,402 | 1 | 5 | null | null | null | null | UTF-8 | R | false | false | 9,392 | r | TF_polII_topGO.R | library(dplyr)
library(data.table)
library(tibble)
library(ggplot2)
library(scales)
require(XLConnect)
options(java.parameters = "- Xmx4g")
xlcFreeMemory()
rm(list = ls())
source(file = "E:/Chris_UM/Codes/GO_enrichment/topGO_functions.R")
path = "E:/Chris_UM/Analysis/21_CL2017_ChIPmix_ULAS_MIX/ULAS_AN"
setwd(path)
... |
c6163e73e21379a348ed22443a59a37f06e2d06d | 2dc56c423107d07d30f7dde3062035f740fde49b | /heterozygosity_new_analysis.R | 9b4fb4f031b05c81bd3394b53a8fcfa327dac6d5 | [] | no_license | tbilgin/pongo_repeats | d1da69381792154ba0f38f3607c50ef521b60e3f | d77fa60aaf8ac7ea6d07c2c2f8fceef987c0334c | refs/heads/main | 2023-06-18T07:45:28.051595 | 2021-07-20T14:33:56 | 2021-07-20T14:33:56 | 355,286,765 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,942 | r | heterozygosity_new_analysis.R | mean(pongo_abelii_heterozygosity$V4)
t.test(pongo_abelii_heterozygosity$V4)
mean(pongo_pygmaeus_pygmaeus_heterozygosity$V4)
t.test(pongo_pygmaeus_pygmaeus_heterozygosity$V4)
mean(pongo_pygmaeus_morio_heterozygosity$V4)
t.test(pongo_pygmaeus_morio_heterozygosity$V4)
hetPongoAbelii = read.table("~/Desktop/pongo_repeats/... |
f8d12cb03ef2dea505cec51f10df165bb4ab4dab | 7f72ac13d08fa64bfd8ac00f44784fef6060fec3 | /RGtk2/man/gtkAboutDialogNew.Rd | 9fea526a2610c76b4217069331c25e0815a18f97 | [] | no_license | lawremi/RGtk2 | d2412ccedf2d2bc12888618b42486f7e9cceee43 | eb315232f75c3bed73bae9584510018293ba6b83 | refs/heads/master | 2023-03-05T01:13:14.484107 | 2023-02-25T15:19:06 | 2023-02-25T15:20:41 | 2,554,865 | 14 | 9 | null | 2023-02-06T21:28:56 | 2011-10-11T11:50:22 | R | UTF-8 | R | false | false | 344 | rd | gtkAboutDialogNew.Rd | \alias{gtkAboutDialogNew}
\name{gtkAboutDialogNew}
\title{gtkAboutDialogNew}
\description{Creates a new \code{\link{GtkAboutDialog}}.}
\usage{gtkAboutDialogNew(show = TRUE)}
\details{Since 2.6}
\value{[\code{\link{GtkWidget}}] a newly created \code{\link{GtkAboutDialog}}}
\author{Derived by RGtkGen from GTK+ documentat... |
8125bb516c61905a8978fcc1eea6b23a954f117e | a9e69d3c4a5590383e6044947b671f8410c5eaf2 | /R/studentAllocation/inst/shiny/app.R | 5c6b8f7e6cae67c1fdacd4c194c37b6b2f362f5f | [
"MIT"
] | permissive | richarddmorey/studentProjectAllocation | 4ea9c3293f9dcc299d06c19917f6d312b86a1743 | d3b58217af85d259c2f5df16719e0061fbe56187 | refs/heads/master | 2023-07-19T21:16:09.073385 | 2023-07-11T17:02:17 | 2023-07-11T17:02:17 | 34,754,193 | 27 | 12 | MIT | 2023-07-11T17:02:18 | 2015-04-28T20:29:25 | JavaScript | UTF-8 | R | false | false | 12,597 | r | app.R | library(shiny)
library(shinydashboard)
library(shinyjs)
library(shinycssloaders)
vals <- reactiveValues(lect_list = NULL,
proj_list = NULL,
stud_list = NULL,
total_effective_cap = NULL,
total_students = NULL,
... |
724e2f6cf3059c179081c216f76c70b768016624 | ea27f667dac71c3ce659e3ec7531a190e65e2d6b | /scripts/b2_gez_tcc_2010_zonal.R | 8214ec6192ad12464db86fc9d8ae86f02e7cf0bd | [] | no_license | lecrabe/tcc_gez_2010 | 58ec36a0a91be08d7a14250fa39abcd3d387e482 | e88638de99e5d49ac7eaf125824cec43e52c27e6 | refs/heads/master | 2022-12-02T07:54:59.263716 | 2020-08-20T07:48:46 | 2020-08-20T07:48:46 | 288,852,391 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,688 | r | b2_gez_tcc_2010_zonal.R | #################### SKIP IF OUTPUTS EXISTS ALREADY
if(!file.exists(tcc_stats_file)){
#############################################################
### RASTERIZE COUNTRY BOUNDARIES ON TCC2010 PRODUCT
#############################################################
system(sprintf("oft-rasterize_attr.py -v %s ... |
f2285eab775d8233cce5fd0065aa318fa460a4df | 1546dc0f386964ec29703e1441595452bbb11385 | /I-dataset/potential_cal/CA_atoms.r | 64c4e065f50d902fb401a7fcdf7efeb91eee8c3d | [
"MIT"
] | permissive | sagarnikam123/bioinfoProject | b86eaf82a8744d4d48772cbd1c4eb25818351fb8 | 3164e82704a28248fd796026bc37f1c681c3cddb | refs/heads/master | 2022-02-06T11:42:58.027408 | 2022-01-26T07:43:18 | 2022-01-26T07:43:18 | 14,169,704 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,238 | r | CA_atoms.r | #for identifying CA atoms only(corrupted ids)
rm(list=ls()) #removing previous objects
library(bio3d)
corrupted_id=NULL #takes CA only atoms id
bengali_joker<-NULL #takes chain breaked id
gangster<-"C:\\Users\\exam\\Desktop\\pdb_chain_veer\\"
farebi<-list.files(gangster)
#for-->1 for whole file... |
4ca0d67517c98e20bca1f0d685692ca8af1197f8 | 9252afa6febef3b46823e0af354f6ecad70a7c7b | /best.R | 6a8016c41b0a0a51d3c1047766e186ae5770f4e4 | [] | no_license | Ujwala89/myRSourceCode | 06563c1d18dd10c26292141aac5c654aa16635a4 | 066ffd639d570fbf5ed68cfbcee285815787c77b | refs/heads/master | 2020-09-14T11:38:47.623036 | 2016-09-12T04:18:24 | 2016-09-12T04:18:24 | 67,973,176 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,258 | r | best.R | best <- function(state, outcome) {
## Read outcome data
## Check that state and outcome are valid
## Return hospital name in that state with lowest 30-day death ## rate
#validate state
if (state %in% state.abb) {}
else{
stop("invalid state")
}
#validate outcome
outcomes <- c("heart at... |
fb9f78ef3db03592fde398f3fee81e0eb3410665 | 3e674458be7851429abf1c92fc2215dab3622104 | /ui.R | 63523966ea3e665c484e902afa887da60c2caec9 | [] | no_license | clavell/ageguess | 30bf2f5a3db2567b6f2a44455a6cc2804eea978c | 5e427a676cf542b1bf6d9b4d30e8d20f93967300 | refs/heads/master | 2020-09-13T19:20:56.755847 | 2017-07-18T06:17:23 | 2017-07-18T06:17:23 | 94,464,185 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 878 | r | ui.R |
# This is the user-interface definition of a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#
library(shiny)
shinyUI(fluidPage(
# Application title
titlePanel("Accurate age guesser"),
# Sidebar with a slider input for number of bins
... |
44386f6614ed8f924eaba219e713f865eafdc459 | 4951e7c534f334c22d498bbc7035c5e93c5b928d | /developers/jones_prec.R | 746ee83a18b1fcc40bea4be3a25d49af3680ad4b | [] | no_license | Derek-Jones/ESEUR-code-data | 140f9cf41b2bcc512bbb2e04bcd81b5f82eef3e1 | 2f42f3fb6e46d273a3803db21e7e70eed2c8c09c | refs/heads/master | 2023-04-04T21:32:13.160607 | 2023-03-20T19:19:51 | 2023-03-20T19:19:51 | 49,327,508 | 420 | 50 | null | null | null | null | UTF-8 | R | false | false | 3,124 | r | jones_prec.R | #
# jones_prec.R, 2 Apr 20
# Data from:
# Developer Beliefs about Binary Operator Precedence
# Derek M. Jones
#
# Example from:
# Evidence-based Software Engineering: based on the publicly available data
# Derek M. Jones
#
# TAG experiment_human developer_belief operator_precedence source-code
source("ESEUR_config.r... |
8131359f0246e545161f78e665cd70da14609c8f | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/genio/man/read_plink.Rd | 235e5b7eddff8e7471353811df9277712f8d1e7f | [] | no_license | akhikolla/testpackages | 62ccaeed866e2194652b65e7360987b3b20df7e7 | 01259c3543febc89955ea5b79f3a08d3afe57e95 | refs/heads/master | 2023-02-18T03:50:28.288006 | 2021-01-18T13:23:32 | 2021-01-18T13:23:32 | 329,981,898 | 7 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,832 | rd | read_plink.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/read_plink.R
\name{read_plink}
\alias{read_plink}
\title{Read genotype and sample data in a plink BED/BIM/FAM file set.}
\usage{
read_plink(file, verbose = TRUE)
}
\arguments{
\item{file}{Input file path, without extensions (each of .bed, .bi... |
9956205b27751f6e631d0b3a3bec2de80c02ed75 | b200d0f16ff7e6bbe72600f8610eae97305f1571 | /R Analytics.R | e7fdd1544a242d6f2b021e64951c483de6d704e4 | [] | no_license | datacodebr/Ciencia_dos_Dados | bede5b5aec6de688c715e128df5b21692f109d40 | 249b836f0ca8f9584a9f8421f40a0b95ea3d49a4 | refs/heads/master | 2020-11-28T12:05:10.917217 | 2019-12-23T19:13:24 | 2019-12-23T19:13:24 | 229,808,474 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 21,043 | r | R Analytics.R | ####################################################################################
#
# Primeiros Passos na Linguagem R
#
#
####################################################################################
#Avisos Paroquiais
### Caso tenha problemas com ... |
425191d47d3b5719353baaa7b72c259bad948174 | ed2892ae0541e9d56f3b234edab712a33a281fe4 | /R/h_kiener3.R | 7553d2cbf673546c544b7a70f6e0919d0d7ff56d | [] | no_license | cran/FatTailsR | c88ccd7d54de67723afb36a652fca1767b4a4caa | 82796785ae65af40ea504c05710f447788afc88a | refs/heads/master | 2021-07-14T21:46:26.585015 | 2021-03-12T08:00:02 | 2021-03-12T08:00:02 | 21,838,335 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 20,881 | r | h_kiener3.R |
#' @include g_kiener2.R
#' @title Asymmetric Kiener Distribution K3
#'
#' @description
#' Density, distribution function, quantile function, random generation,
#' value-at-risk, expected shortfall (+ signed left/right tail mean)
#' and additional formulae for asymmetric Kiener distribution K3.
#'
#' @param x ... |
985abea1068c0f2f599602a309866c4d155e699d | bff40d50e61358a0c40ed96c76d856247221f786 | /AnamulHaque_Assignment2.R | a2556a05d8642e4c7f2dcdc657f4f27f77d26e3b | [] | no_license | anamulmb/Statistics-in-R-Shiny | 2faa4f63ad8468de67bdff2037fd5d6813ed6691 | 55481a4ba5bffed49820f37d435be9457b5b8822 | refs/heads/master | 2023-03-15T00:06:32.195703 | 2021-03-24T14:25:23 | 2021-03-24T14:25:23 | 85,979,281 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 907 | r | AnamulHaque_Assignment2.R | #Calculates 1+ 2
1 +2
#Write a string Beat LSU
print ('Beat LSU', quote = FALSE)
#Assign the value 15 to a variable named wins
#Your script should print the variable wins to the screen when run
wins <- 15
print(wins)
#Your script should print Your Name
#On a new line your script should print Your Degree ... |
f5f5bce342ea00f6d6b3db24183f5c38a1eaafd9 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/dsa/examples/ts2xts.Rd.R | c042455d3f207af84fd5a8caa900afa0d4858840 | [] | 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 | 165 | r | ts2xts.Rd.R | library(dsa)
### Name: ts2xts
### Title: Change ts to xts
### Aliases: ts2xts
### ** Examples
ts2xts(stats::ts(rnorm(1000, 10,1), start=c(2001,1), freq=365))
|
3a632638fbccbc4571f73e4d7644ebe3a173cbb9 | e5ebddef173d10c4722c68f0ac090e5ecc626b8b | /IL2RA/bin/normalmixEM2comp.R | 201ae21e07c935be40650e361d9f975aa8347076 | [] | no_license | pontikos/PhD_Projects | 1179d8f84c1d7a5e3c07943e61699eb3d91316ad | fe5cf169d4624cb18bdd09281efcf16ca2a0e397 | refs/heads/master | 2021-05-30T09:43:11.106394 | 2016-01-27T15:14:37 | 2016-01-27T15:14:37 | 31,047,996 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 735 | r | normalmixEM2comp.R | #!/usr/bin/env Rscript
suppressPackageStartupMessages(library(mixtools))
suppressPackageStartupMessages(library(cluster))
source('~nikolas/bin/FCS/fcs.R')
option_list <- list(
make_option(c("--fcsFile"), help = ""),
make_option(c("--channel"), help = ""),
make_option(c('--RData'), help='')
)
OptionParser(option_list... |
461e23baaf1dd90d003f62ee7d92ad44f72c807a | 16e8b1f2886d4dad26757814ce5c65382bd1f829 | /man/Rat.Rd | 1b12c89d59542d5e0af654e3702c690cff70a47d | [] | no_license | richierocks/gpk | f14d80e87b22e0407488c3b24956d1e35c53ae65 | 9a437680da57d8d2cc03fd5997981c0ddf6e6e77 | refs/heads/master | 2021-01-21T21:09:30.969109 | 2017-05-24T18:20:45 | 2017-05-24T18:20:45 | 92,310,887 | 2 | 0 | null | 2017-05-24T15:59:51 | 2017-05-24T15:59:51 | null | UTF-8 | R | false | false | 1,060 | rd | Rat.Rd | \name{Rat}
\alias{Rat}
\docType{data}
\title{
Study of rat burrow architecture
}
\description{
Bandicoot rats live in underground burrows dug by them. 83 burrows were excavated and measured. However, by accident, only the marginal distributions were retained while the original data on joint distribution was lost. Check... |
667f081134e726c4e3bb225f3bc6fc709dd768d7 | 590142f535831def89b5b2d0f6ac1d47b8306850 | /man/ParallelBlock-class.Rd | bc424783548a57d346ba1e394a9b4f2a155e2f67 | [] | no_license | jfontestad/makeParallel | 2b62704c9e26477bc89d505de313ea07aaebdcca | 6e43f34f51a23692907ec1563d3d47a8e189d7bf | refs/heads/master | 2023-01-13T03:27:16.260825 | 2020-11-17T16:41:04 | 2020-11-17T16:41:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 361 | rd | ParallelBlock-class.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/AllClass.R
\docType{class}
\name{ParallelBlock-class}
\alias{ParallelBlock-class}
\alias{ParallelBlock}
\title{Code to run in parallel}
\description{
Code to run in parallel
}
\section{Slots}{
\describe{
\item{\code{export}}{names of objects... |
b7d75e47c4c8160d4cd5cee0f2d02673dc2397ff | 3b2741d6fc9a489dcd394f9f708f5554db1a1adb | /PA1.R | bac39e77c90d009018e30152414a6f604310217d | [] | no_license | FranciscoAlonso/RepData_PeerAssessment1 | def9d1d48b768a48af8be8bf7e6e76420202c7da | 68af630305e73fbff2116fd396a5c9a7e83e774a | refs/heads/master | 2020-12-24T10:23:08.721655 | 2015-08-16T21:01:24 | 2015-08-16T21:01:24 | 40,564,632 | 0 | 0 | null | 2015-08-11T20:51:43 | 2015-08-11T20:51:42 | null | UTF-8 | R | false | false | 2,264 | r | PA1.R | PA1 <- function()
{
library(lubridate)
library(dplyr)
steps <- read.csv("activity.csv")
#convert to date format
steps$date <- ymd(steps$date)
steps <- na.omit(steps)
allDates <- seq(from = min(steps$date), to = max(steps$date), by = "day")
stepsPerDate <- as.data.frame(allDates, row.names(c(... |
070744fb954be1040468553efd672b6861f08468 | 9d126e2d47795f1d45cf3bd400a5547b9e6e6b77 | /eQTL_GWAS_riskSNPs_n596/create_eqtl_table.R | d16bbbf9c55240cc08c7f40911d80e1265a9f145 | [
"MIT"
] | permissive | LieberInstitute/dg_hippo_paper | f3bf015f14da7a43ddcceb6992033600daa237d7 | b2694e0083e96562cfe681d96459a3c670e6ccd8 | refs/heads/master | 2021-07-09T05:35:54.995464 | 2020-09-14T17:03:53 | 2020-09-14T17:03:53 | 157,881,996 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,736 | r | create_eqtl_table.R | ##
library(jaffelab)
library(IRanges)
library(SummarizedExperiment)
#####################
##### Subset of 881 SNPs from PGC
#####################
################
## load eQTLs
load("eqtl_tables/mergedEqtl_output_dg_raggr_4features.rda", verbose=TRUE)
dg = allEqtl[allEqtl$FDR < 0.05,]
load("eqtl_tables/mergedEqtl_o... |
cdb2111e14f7367fe1742c9a9cdaf4486c6c8882 | 919e3e0a88cf0099a43e0bc0b31eac60c8074bf8 | /tests/testthat/test-prepareData.R | 0f6a41dc7bfc1868eb61c1fa45dcac4c40503474 | [] | no_license | itikadi/EMOGEA | 929e86a91f09c24b6e7711f87f62f3ccf468151a | 91dd507efe60070d115b63382a86e423ab228e6f | refs/heads/master | 2023-04-17T00:01:28.534769 | 2021-04-24T15:25:55 | 2021-04-24T15:25:55 | 291,812,012 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 949 | r | test-prepareData.R | # Libraries
library(data.table)
# Select the folder where the inputs and expected outputs are located
rdsPath <- "../testdata"
# Test prepareData
testthat::test_that("Test prepareData",
{
# Read files which contain the inputs
expressionData <- fread(file.path(rdsPath, "input_expressionData.csv"))
metaData <- fr... |
d546596e47e1cefe5c206ca118854cddcedb9056 | 7466dbb3f016774d6cb1ddeb142de1edae496378 | /man/tf2doc.Rd | a0e54f5f6ddebde3f80e9c64610258aeb46e7c2b | [] | no_license | cran/chinese.misc | 0dc04d6470cff7172c76f3a735986ef7128c74da | 369fd6b193e5d969354a31e568fabe53cb596c8c | refs/heads/master | 2021-01-19T09:55:21.948813 | 2020-09-11T20:50:03 | 2020-09-11T20:50:03 | 82,150,007 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 981 | rd | tf2doc.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tf2doc.R
\name{tf2doc}
\alias{tf2doc}
\title{Transform Terms and Frequencies into a Text}
\usage{
tf2doc(term, num)
}
\arguments{
\item{term}{terms that you want to rewrite into a text. A character vector is preferred, but
matrix, ... |
8bb5fab7d3277b7d27920201855e08911ce951ca | c2d29768d7a4262e1cabf6688df0e3b290103df3 | /Assignment-1/R code.R | 45fd5be18060b8024e546cf7719ebb27e0180d20 | [] | no_license | Utsav37/Data-Mining | 4913ab51ffb588f59b8f161d738f12a5b18e3ce9 | d8d0cf7297b5b4bf3b6f531b5122968975f37508 | refs/heads/master | 2020-04-20T01:37:31.693421 | 2017-12-28T00:58:32 | 2017-12-28T00:58:32 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 75 | r | R code.R | x <- seq(1,50,by=2)
y <- 2*x - 30
png("Abhishek plot.png")
plot(x,y)
|
0f297e7fed65cdbca10cafdb38602e5175720c43 | 738589305032d5a35d7c433969377bacf7284983 | /man/read.digital.surf.file.Rd | 52aad2a91d179b98fb40a6378adfeb8450eb0603 | [] | no_license | tanyanap4/x3pr | 4dd9451cb6b662db4c4aecf504c24c80dcce6947 | 517a04d88ecaad5336ff9c5a7c6f46b1a31763c4 | refs/heads/master | 2021-01-10T18:51:07.192671 | 2015-01-14T21:33:23 | 2015-01-14T21:33:23 | 29,158,058 | 0 | 0 | null | 2015-01-14T20:53:45 | 2015-01-12T21:33:44 | R | UTF-8 | R | false | false | 595 | rd | read.digital.surf.file.Rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/read.digital.surf.file.R
\name{read.digital.surf.file}
\alias{read.digital.surf.file}
\title{Read in a Digital Surf file wrapper. Just specify the path to the
.sur file.}
\usage{
read.digital.surf.file(file.path)
}
\arguments{
\item{f... |
fff7423f51a626e824d8917fb33f4ded77a9b33b | 1a12b5865f377c8eaaa0cbf5cd6b4a1cf5d00810 | /Rplot02.R | ae5baf5efac0de77df1583b8b57ff4807b6c4a67 | [] | no_license | willk1990/ExData_Plotting1 | 810dbe284fe2487425a24ff0b509bced56e2a395 | c20b07f0acf4394344120eb304ce51d1b4229e57 | refs/heads/master | 2020-11-29T15:28:39.407016 | 2017-04-15T17:35:34 | 2017-04-15T17:35:34 | 87,478,983 | 0 | 0 | null | 2017-04-06T22:01:09 | 2017-04-06T22:01:09 | null | UTF-8 | R | false | false | 627 | r | Rplot02.R | pwr <- read.table("household_power_consumption.txt",header = TRUE, sep = ";",as.is = c(3,4,5,6))
pwr <- subset(pwr,pwr$Date == "1/2/2007" | pwr$Date == "2/2/2007")
time2 <- paste(pwr$Date,pwr$Time)
time2 <- strptime(time2, format = "%d/%m/%Y %H:%M:%S")
pwr$Global_active_power <- as.numeric(pwr$Global_active_pow... |
a59c645d54dd7a616af0ed4da3715952093f6937 | 2d0c8242f25ae6cc9a0eaf4097eca9e9d9f42b62 | /foieGras.R | 08b21aab00a8042b7b6c5fa32b6e8812a3b5c1b9 | [] | no_license | makratofil/crc-hawaii-tags | a51e33a181129a95c1e415f9791169a302b84266 | 090ec18121c4fce2dbe79a86d43d463783ba98a9 | refs/heads/master | 2022-05-19T12:01:36.654699 | 2022-05-11T15:43:55 | 2022-05-11T15:43:55 | 249,754,977 | 2 | 3 | null | 2021-02-16T23:19:44 | 2020-03-24T16:08:42 | R | UTF-8 | R | false | false | 6,114 | r | foieGras.R | ##########################################################
# foieGras: fit continous-time random walk or
# correlated random walk models to
# animal movement data
# Michaela A. Kratofil, Cascadia Research
# Updated: 06 AUG 2020
#######################################################... |
876e417ea0f00d47b03ec68650c6a3322d8bfaab | b781976b9af252036f3a2bd56295aa39a12f79d3 | /man/neuron_pairs.Rd | 5c6da22422ab39219df3d94d5729d0656389f083 | [] | no_license | natverse/nat.nblast | 18ac30ad38bd3d37b41565183aa012cab43fb6a3 | f582c7d1eca42c09b3ebef8009dc7129809ea8ab | refs/heads/master | 2023-06-26T22:12:18.232134 | 2023-06-13T18:13:28 | 2023-06-13T18:13:28 | 19,026,348 | 7 | 1 | null | 2023-01-12T17:33:14 | 2014-04-22T10:54:53 | R | UTF-8 | R | false | true | 908 | rd | neuron_pairs.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/smat.r
\name{neuron_pairs}
\alias{neuron_pairs}
\title{Utility function to generate all or random pairs of neurons}
\usage{
neuron_pairs(query, target, n = NA, ignoreSelf = TRUE)
}
\arguments{
\item{query, target}{either \code{\link{neuronlis... |
466567a7cd6a9359a733c168744a031db9dc42da | 08b154beac70fc61b20550e4969d5eaa82003525 | /demoShiny/server.R | 3bdd268f10e779cddb8c0d28091ae23b2503e011 | [] | no_license | mcSamuelDataSci/R-visual-display-workshop | 01a9df9498626736ef34d965a6278516d6d0c9bb | 368154028e5e6440fad46151dec1745523d38daf | refs/heads/master | 2020-04-02T05:24:40.178075 | 2019-11-01T21:18:58 | 2019-11-01T21:18:58 | 154,074,323 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 119 | r | server.R | shinyServer(function(input, output) {
output$myPlot1 <- renderPlot( deathTrendPlot(input$myCounty))
})
|
1a824b7b8fdd051dc692dad124a785f56f6fef0d | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/MVar/examples/MFA_English.Rd.R | a5a1d662f0576aaec5495a9a77badbfdb0095cb4 | [] | 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 | 580 | r | MFA_English.Rd.R | library(MVar)
### Name: MFA
### Title: Multiple Factor Analysis (MFA).
### Aliases: MFA
### Keywords: Multiple Factor Analysis MFA MFACT
### ** Examples
data(DataMix) # mixed dataset
Data <- DataMix[,2:ncol(DataMix)]
rownames(Data) <- DataMix[1:nrow(DataMix),1]
GroupNames = c("Grade Cafes/Work", "Formation/Dedi... |
dec0c4f6f565d064f92a125ee844c028da6b0ee6 | 0d821faa15751b8ede906b2fe870932a118efc00 | /Riparian_functions_v1.r | 907fbf8adeb78e0f0cfc7fa08ea6f1a4bd690b8b | [] | no_license | GeospatialDaryl/R_Functions | 2b217aca13d763290216542ba0d5d92f1bdf7dc8 | 61cd6466926e4fc7bf1a07614bdbcfbac7c16ad4 | refs/heads/master | 2021-01-20T03:17:13.379698 | 2017-05-17T23:23:05 | 2017-05-17T23:23:05 | 89,520,257 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,613 | r | Riparian_functions_v1.r | # http://stackoverflow.com/questions/21815060/dplyr-how-to-use-group-by-inside-a-function
# For programming, group_by_ is the counterpart to group_by:
#
# library(dplyr)
#
# mytable <- function(x, ...) x %>% group_by_(...) %>% summarise(n = n())
# mytable(iris, "Species")
# # or iris %>% mytable("Spec... |
9126da9650e97bd7b5585213e4cbc740f5252a59 | b4bba5708aa80327e5a47930fd3483236a4427ad | /man/start_end_dates.Rd | 49a350512913c48be121d66586d1dc3309a5dbd8 | [
"MIT"
] | permissive | PaulESantos/snowpack | bffbffa0dec68bb4f5825d4568fa3d75cc6a7c40 | 7b564e31df5685dc4f66645ba6c588291ae0fd11 | refs/heads/main | 2023-03-20T19:58:06.891347 | 2021-03-19T03:22:47 | 2021-03-19T03:22:47 | 343,623,930 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 815 | rd | start_end_dates.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/start_end_dates.R
\name{start_end_dates}
\alias{start_end_dates}
\title{Find start and end dates of HOBO data}
\usage{
start_end_dates(df, ...)
}
\arguments{
\item{df}{A data.frame formatted as the example dataset. Review
hobo_rmbl_data to se... |
dc7a4542bd522a1e3967d154d8fa09c5fc6011f0 | 6e573b701339dd0a470df3a666e6b176bfd59bf7 | /cachematrix.R | e7a0149f2151f4bf53b09e89b8d8518d415eff2a | [] | no_license | kenburkman/ProgrammingAssignment2 | 50185afa80399a125a903ea823936ab1c0bc2dab | 3c6a7c010ac86b8a5a143f556114147295989fcc | refs/heads/master | 2021-01-18T05:59:01.388468 | 2016-07-02T14:05:21 | 2016-07-02T14:05:21 | 62,424,507 | 0 | 0 | null | 2016-07-01T23:17:17 | 2016-07-01T23:17:16 | null | UTF-8 | R | false | false | 1,015 | r | cachematrix.R | ## These two functions allow the user to solve and cache
## the inverse of a matrix so that it can be recalled later
## without the need to recalculate it.
## this function enables you to set and get the matrix and to
## set and get the matrix's inverse.
makeCachematrix<-function(x=matrix()){
i <- NULL
... |
a3a110a852c194f9c36dcf16f3d12ab08b904336 | a3a81c268a8e7bd29e3b5e007f521078785e9305 | /server.R | 8fa922da50a2f2a2d3311aabfdcd267bdbb94c23 | [] | no_license | mfatemi/Developing-Data-Products-Shiny | a23481196c93ea395167b8b0404cca394b099af3 | 5293460e547cc01146b3d2aadc941ab7e3992026 | refs/heads/master | 2020-05-19T10:08:06.905881 | 2015-09-22T18:51:53 | 2015-09-22T18:51:53 | 42,950,929 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 376 | r | server.R |
shinyServer(
function(input, output) {
output$text1 <- renderText({input$text1})
t<-reactive(rnorm(input$text1))
output$sum <- renderPrint({
t<-t()
summary(t)
})
output$distPlot <- renderPlot(
{ t<-t()
... |
332642ffa69506f6aece64714c374aa69f34d700 | 49ddfd7fd6503e6156a5db40911aa340a06685b0 | /Basic_statistics_genotype_data/Calculating_basic_satistics_validated_SNPs.R | 2d2fe69192d045e581294c79ef6f5c07eb653df5 | [] | no_license | MarineDuperat/Resilience_white_spruce | c718ef70f59331bbd5e2cc3332a7009d7c23d90c | d58037299a83dda2201986562a3ef7deefcefffe | refs/heads/master | 2022-04-10T17:55:06.413959 | 2020-03-11T19:40:41 | 2020-03-11T19:40:41 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,934 | r | Calculating_basic_satistics_validated_SNPs.R | #############################################################################################
## Introduction
#############################################################################################
#Code for
#"Adaptive genetic variation to drought in a widely distributed conifer
#suggests a potential for incr... |
f0d0fee29cfa2f0b59b609029e7e7d4446a5c43c | 9caf26039acdcdb74ccf8025bfdff0c3ef1b190b | /Kumejima_Analysis/gakuGeneral_functions.R | 7d96e7515b29d76fdaf9600c80cd11a6d76a9055 | [] | no_license | Kohsuke1031/Test2 | 5ff095f0eeade76a73a08bb89b3ae3b2fe139937 | c21719638ded9836bc29023576430d5cf87fe1e6 | refs/heads/master | 2023-06-04T20:13:39.042971 | 2021-06-21T07:10:33 | 2021-06-21T07:10:33 | 378,777,345 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 756 | r | gakuGeneral_functions.R | ## gaku's fucntions
## 1 縦書き用フォーマット
#h ttps://id.fnshr.info/2017/03/13/r-plot-tategaki/
tategaki <- function(x){
x <- chartr("ー", "丨", x) # 長音符の処理
x <- strsplit(split="", x)
sapply(x, paste, collapse="\n")
}
#df_paths = list.files(path = "./gakuLab_with_Yasui_san/Ishikawa_Analysis/Ishikawa_Data",full.names... |
136611cec100ea67ee86a1ed00bae628ff43466b | 5d690f159266b2c0f163e26fcfb9f9e17a0dc541 | /GET/R/crop.r | e43808423faeff856c58952fcd36aa71356f1b59 | [] | no_license | albrizre/spatstat.revdep | 3a83ab87085895712d7109c813dcc8acb55493e9 | b6fc1e73985b0b7ed57d21cbebb9ca4627183108 | refs/heads/main | 2023-03-05T14:47:16.628700 | 2021-02-20T01:05:54 | 2021-02-20T01:05:54 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,159 | r | crop.r | #' Crop the curves to a certain interval
#'
#' Crop the curves to a certain interval
#'
#'
#' The curves can be cropped to a certain interval defined by the arguments r_min and r_max.
#' The interval should generally be chosen carefully for classical deviation tests.
#' @param curve_set A curve_set (see \code{\link{cre... |
2dec0b49ceacf123a8de7d3a8194017c2cb56790 | 30e573840e35fac8e0fd7426dbed415a294d80bd | /Figure 11.4.R | ffcd3c1766ce0614ffefbc2d74bb53e11d608dba | [] | no_license | henrylankin/stat6304 | fbd9490cd00fc9b1ad9b08915f2c30c5147d3f8f | 2fcdd0590ba1e141d75568f13f50c772e7b93ff8 | refs/heads/master | 2021-01-23T05:14:43.235965 | 2017-03-27T04:24:17 | 2017-03-27T04:24:17 | 86,289,594 | 0 | 0 | null | 2017-03-27T04:24:18 | 2017-03-27T03:59:58 | null | UTF-8 | R | false | false | 750 | r | Figure 11.4.R | #import data
ex11.4 <- read.csv("~/Desktop/School/6304/Data Sets/ASCII-comma/CH11/ex11-4.TXT", quote = "'")
#View(ex11.4)
#scatterplot
plot(ex11.4$x, ex11.4$y, xlab = 'x', ylab = 'y', main = 'Figure 11.4: x vs. y')
#regression line
regression.line <- lm(ex11.4$y~ex11.4$x)
abline(regression.line)
regLine.summary <- su... |
3dc6d0d5d2b796611fd9749a0d636e5cdd3c2477 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/available/examples/suggest.Rd.R | 6cbc9b1cc360e2c9377565430ee373833c8db259 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 512 | r | suggest.Rd.R | library(available)
### Name: suggest
### Title: Suggest a package name based on a development package title or
### description
### Aliases: suggest
### ** Examples
## Not run:
##D # Default will use the title from the current path.
##D suggest()
##D
##D # Can also suggest based on the description
##D suggest(fi... |
be2d2fb8d44dc3e63bc2e101173402b0d1f2980c | 5d18784db64de6f1355e90b7b0a787c0707ddd35 | /R/ggplot.bfastIR.R | 156bc03e47a457cc956eb5f2ae0eb63c36f88de8 | [] | no_license | dondealban/bfastApp | 61b13523a3ecdf4c9554f66f55d11c35127bab25 | 33416fc025451f3794370127b316079b15a3dcba | refs/heads/master | 2021-05-30T12:25:01.824464 | 2015-07-09T08:02:34 | 2015-07-09T08:02:34 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,254 | r | ggplot.bfastIR.R | ggplot.bfastIR <- function(x, seg = TRUE, order, formula) {
ggdf <- x$df
ggdf[,'breaks'] <- NA
ggdf$breaks[x$breaks$breakpoints] <- 1
xIntercept <- ggdf$time[ggdf$breaks == 1]
gg <- ggplot(ggdf, aes(time, response)) +
geom_line() +
geom_point(color = 'green') +
geom_vline(xintercept = xIn... |
89d80735a003703d18098db0cc523bc5f55f3fe7 | c7c558f492eae205ce72b4c2361827a79a86e65d | /UPDE/ATACseq/FSC/30_ATAC_merge_counts.R | 4dab00b2079a714d2d155f62d4ea9d6fdfdfbb7f | [] | no_license | jpezoldt/UDPE | 6094ddb629939abe2cc93d7ee68711cea8f0db4e | 262c7c87a36ae4598ed5927ac64cf52e6576000c | refs/heads/master | 2021-07-13T02:06:03.302301 | 2019-01-11T11:01:02 | 2019-01-11T11:01:02 | 143,868,496 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,262 | r | 30_ATAC_merge_counts.R | # Author: Vicnent Gardeux
# Adapted by: Joern Pezoldt
# 12.07.2018
# Function:
# 1) Merges tables of count per peak from homer ATAC-seq pipeline, by id
#Libraries
require(data.table)
# Input required: Set path to directory with the homer .txt files (output of annotatedpeak.pl)
setwd("/home/pezoldt/NAS2/pezoldt/Analy... |
ee884eaaf8d93dd000db0c64a7e76c8675f404d1 | 149bc111fbbc1d4772d4af1f5335b83e3f868271 | /tests/testthat.R | 807b2edb853b07455867d4b8a99e757d9a926336 | [] | no_license | NiklasTR/microbiomefhir | 157fa380caec7c0a114bd11e6023d40465440c92 | 6078851064ebe0ffe8840ed7c83006b79c07b6a2 | refs/heads/master | 2020-04-06T16:17:15.029430 | 2019-06-20T11:07:53 | 2019-06-20T11:07:53 | 157,613,751 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 70 | r | testthat.R | library(testthat)
library(mirobiomefhir)
test_check("mirobiomefhir")
|
5735d42d1889cea72f0684480781c4796d434c7b | 006d56a4efa0a566ea9aeaa2b179d0a765d6ee4a | /appDevelopment_nestwatch/appNestwatchTechnicianInterface/fieldOptions.R | 056d05837e37137fff3dae4359c4f64ffe2d2f34 | [] | no_license | bsevansunc/shiny | 83f935fefa33d4118802dfb48f60c5892de2c028 | 5da0768d93d2937f1baad2c88c9f7907107ef87f | refs/heads/master | 2021-01-10T12:53:59.057260 | 2017-12-14T19:03:13 | 2017-12-14T19:03:13 | 47,638,868 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,943 | r | fieldOptions.R | #---------------------------------------------------------------------------------*
# ---- VISIT ----
#---------------------------------------------------------------------------------*
# Define fields for visit data:
visitFields <- c('hub', 'site', 'observer',
'longitude', 'latitude', 'accuracy', 'l... |
a8b21d874c8008e967bb4a8abf02c35c9ae0c2cc | f8161c1763d3430e606b1afd6b57e35b33604f91 | /man/xgx_stat_smooth.Rd | b842f8f6b40bb8adcfb1612f1430e4745d990bde | [
"MIT"
] | permissive | Novartis/xgxr | f9d99dba43afc439e662e2a4bc56455c8cc7144b | 287d64155ae3d1299befb90dc846b9189db443ad | refs/heads/master | 2023-08-31T10:43:54.993048 | 2023-08-18T22:17:42 | 2023-08-18T22:17:42 | 194,325,753 | 14 | 10 | NOASSERTION | 2023-08-18T22:17:43 | 2019-06-28T19:42:53 | R | UTF-8 | R | false | true | 8,498 | rd | xgx_stat_smooth.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xgx_stat_smooth.R
\name{xgx_stat_smooth}
\alias{xgx_stat_smooth}
\alias{xgx_geom_smooth}
\alias{xgx_geom_smooth_emax}
\title{Wrapper for stat_smooth}
\usage{
xgx_stat_smooth(
mapping = NULL,
data = NULL,
geom = "smooth",
position = "i... |
d4aea3c9b87a6497dcf131f9fb1b14309bcd3ec2 | c24c33d7aec329b5617b7a887d515dcde6d16d5b | /crispr_db/validateThierFinding.r | 5500a032feecad718839cf4f67db907733b5e055 | [] | no_license | cshukai/apache_spark_crispr | 71814690d86c9ba26c39c727b726b06b000be322 | dc5dee4eebd2ad3d2957ef5ed209e161a44c4139 | refs/heads/master | 2020-05-14T21:00:04.538391 | 2016-07-22T19:16:56 | 2016-07-22T19:16:56 | 181,954,474 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,794 | r | validateThierFinding.r | ## parse into proper format
without=read.table("noCrisprSpecies.txt",quote = "",header=F,sep="|")
temp=tolower(without[,2])
temp2=gsub(pattern=" ",replacement="_",temp)
temp3=gsub(pattern="\'",replacement="",temp2)
temp4=gsub(pattern="\\/",replacement="_",temp3)
temp5=gsub(pattern="-",replacement="_",temp4)
temp6=gsub... |
960af1a551043f1bc5faf5279584f4a7bfd36e34 | 2bec5a52ce1fb3266e72f8fbeb5226b025584a16 | /dng/man/splitt_moments.Rd | 557ba07bd3e242e423d01943782e6ff309b23a9b | [] | no_license | akhikolla/InformationHouse | 4e45b11df18dee47519e917fcf0a869a77661fce | c0daab1e3f2827fd08aa5c31127fadae3f001948 | refs/heads/master | 2023-02-12T19:00:20.752555 | 2020-12-31T20:59:23 | 2020-12-31T20:59:23 | 325,589,503 | 9 | 2 | null | null | null | null | UTF-8 | R | false | true | 2,176 | rd | splitt_moments.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{splitt_kurtosis}
\alias{splitt_kurtosis}
\alias{splitt_moments}
\alias{splitt_mean}
\alias{splitt_skewness}
\alias{splitt_var}
\title{Moments of the split-t distribution}
\usage{
splitt_kurtosis(df, phi, lmd)
... |
dfa32b8e0c900bf33c1114f9ec36ad179eec37d7 | 6dce20dd72eb9eb809c0972bd0f5d479b20f71e6 | /R/geom_timeline_label.R | a65c46e85aa09607bb0cdfe2b5ed880ebca55b9c | [
"MIT"
] | permissive | staedi/eqviz | 9a41ef3567085d4ee436c07f67222970d5c07764 | 6bd6533e76a4c593658203260ca538e8b60f1e05 | refs/heads/master | 2022-12-08T02:10:29.469779 | 2020-08-31T00:30:44 | 2020-08-31T00:30:44 | 274,668,542 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,856 | r | geom_timeline_label.R | library(ggplot2)
library(dplyr)
#' GeomTimelineLabel: Geom for adding text labels of earthquake locations on the timeline
#'
#' This Geom is the optional addon for GeomTimeline Geom element.
#' This aims to give extra information of locations by adding text labels on top of the pointsGrob element.
#' The text is 45 de... |
981bda315175cfecbe80d796abaddb086741f36b | 6c51327c2cd25f6ac64b0e07983283f90f31e1bc | /1_plot_scripts/winter/winter_DJFMP.R | 4ebbb693fc03bc0864ac9755c5c33f1617ab0055 | [] | no_license | lmitchell4/Status-and-Trends | 481bf9b957e9afbd172d7cba8db0f036622c7ab2 | 9c19fe2917496306cc812e27764f0aa2d6b5d6b3 | refs/heads/master | 2022-10-03T07:58:30.961149 | 2022-07-19T22:46:57 | 2022-07-19T22:46:57 | 180,163,867 | 0 | 0 | null | 2019-04-08T14:13:12 | 2019-04-08T14:13:11 | null | UTF-8 | R | false | false | 3,874 | r | winter_DJFMP.R | ## Winter = Dec, Jan, Feb
## See a copy of the document "#22 Metadata (Updated May 30, 2019).doc" for reference.
source("setup.R")
library(lubridate)
##########################################################################
## Read in data:
load(file.path(data_root, "chippsData.RData"))
##########################... |
a522e7d76356aa6fe66791de58a83ecd5a406208 | d42b70a85ba00da44ce923e1320f27ec4f6a874c | /man/GeoLiftMarketSelection.Rd | 52b533174f1afcab6f8c9ae0f1110e4dbae1162b | [
"MIT"
] | permissive | jesse-lapin/GeoLift | b8e6e20595e96c2cc700a16d802cc282aff7b391 | f7c36e566720ec206bb0f19f6ba865e63601aefd | refs/heads/main | 2023-08-27T13:16:17.182241 | 2021-10-29T20:57:25 | 2021-10-29T20:57:25 | 423,981,596 | 0 | 0 | MIT | 2021-11-02T19:59:08 | 2021-11-02T19:59:07 | null | UTF-8 | R | false | true | 6,342 | rd | GeoLiftMarketSelection.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GeoLift.R
\name{GeoLiftMarketSelection}
\alias{GeoLiftMarketSelection}
\title{GeoLift Market Selection algorithm based on a Power Analysis.}
\usage{
GeoLiftMarketSelection(
data,
treatment_periods,
N = c(),
X = c(),
Y_id = "Y",
lo... |
809325ffe7b464687097f0d8166e4b925c06e198 | 77a7a3e311fa2dc0d24388061da7c406b48daf86 | /R/_custom_buffer_points.R | 54752ba7a0075d80d633678f135fd086277cf7e4 | [] | no_license | federicotallis/h3forr | a6133260e0794e318597f3ee7b6a435cf4a8297e | 5c74feb961b6dd00319829e935178997e5e84c67 | refs/heads/master | 2023-03-28T05:50:32.245915 | 2020-12-05T08:43:08 | 2020-12-05T08:43:08 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 434 | r | _custom_buffer_points.R | buffer_points <- function(points, res = 7, radius = 1, f = NULL) {
if(is.null(f)) f <- function(radius, distance) 1 - distance * 1 / (1 + radius)
geo_to_h3(points, res) %>%
k_ring_distances(radius) %>%
purrr::reduce(rbind) %>%
dplyr::mutate(weight = f(radius, distance)) %>%
dplyr::group_by(h3_index... |
a0cfaf46ec323cd55ff3d87496f573dce2b2d750 | 43fc9173f16d6806446afec2c370414471b39f3b | /2a_apply_partykit_onPax.R | b77a7e1202546d7f5a13f6650cf8739eb5c0a262 | [] | no_license | dkremlg/el | fbba0c63b22ede2b293916dcd9bde9bd7e1bf3c5 | 1be12e761dadc285fc86ff1aae0f504d93cbda24 | refs/heads/master | 2020-05-17T10:50:13.226132 | 2019-06-25T22:40:09 | 2019-06-25T22:40:09 | 183,665,858 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,222 | r | 2a_apply_partykit_onPax.R | library(partykit)
path='C:/Users/35266/Documents/Python Scripts/el/'
Data=read.csv(paste0(path,'Intermediate_Output/R_Training_Pax.csv'))
Data[Data[,'NumPax']<0,'NumPax']=0
class(eq.mob <- NumPax ~ 1 + Dprio | dday + dtime + Direction + month)
curve.model <- glmtree(
eq.mob,
data = Data,
family = poisson, ... |
eec8e4f0286dd93ef6257ea522a14471ec205144 | 631ced5674d04dc347e8127a99eff7e3d91773c0 | /beyond_gridlock/read_indc.R | 6a1e8a3c845e9bb1608fbb0bf017ba95fb1b3cf5 | [
"MIT"
] | permissive | gilligan-ees-3310/climate-change-lecture-scripts | 7864ed93d8078468bbb513d2e470384f2e24a54b | d7fe0ba460ad3c1953458deceb93b1313bf2832a | refs/heads/main | 2023-03-29T12:38:34.497472 | 2021-04-05T06:19:47 | 2021-04-05T06:19:47 | 348,622,200 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,219 | r | read_indc.R | library(readr)
library(dplyr)
library(stringr)
library(tidyr)
library(ggplot2)
data <- read.csv('data/PBL_INDCs.csv', header = F, as.is=T,
na.strings = c('',' ','-','NA'),
colClasses="character", fill=TRUE, strip.white = TRUE)
n <- data %>% head(1) %>% unlist %>% unname %>% str_repl... |
d388272ab9f7a5c0b8bc1f9a5011b732d6bbd03e | b30a6a9d69305509e197bd36d5307578a05ad46f | /formattingfiles.R | b602f4890215826d47d2bdf875bdb8adb61cc686 | [] | no_license | amwootte/analysisscripts | 49b4d6736d1701805a960425f96d01e7397ef852 | 9ab5dd1a7659664daf652c0138510e5a3644ee62 | refs/heads/master | 2022-07-20T05:09:10.418987 | 2022-07-06T15:02:10 | 2022-07-06T15:02:10 | 116,304,534 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 786 | r | formattingfiles.R | ##################
#
# GeoTIFF write test with 3^5 output
library(ncdf4)
library(rgdal)
library(raster)
library(rasterVis)
library(maps)
library(maptools)
var = "heatwaves"
scen = "rcp26"
test = nc_open(paste("/data2/3to5/I35/ens_means/",var,"_ensmean_absolute_2041-2070.nc",sep=""))
vardata= ncvar_get(test,paste("pr... |
f7c0e3ff31adfeb160a936629e9b85bf49263afc | 38d928387b7ddce39d994af248efab9f34bab684 | /generalize/man/r.value.Rd | 0c8111588280ad16411f520cc4edfa641893e988 | [] | no_license | tamartsi/generalize | 2d33d73565fde136eb0334be52da6c18641fd73f | e09b55ad2e8f845724c40ec392e1a16e5f92da5a | refs/heads/master | 2021-01-10T02:51:04.734117 | 2016-09-21T00:43:46 | 2016-09-21T00:43:46 | 48,065,612 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,013 | rd | r.value.Rd | \name{r.value}
\alias{r.value}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
r-value computation
}
\description{
The function computes r-values given two vectors of p-values from primary and
follow-up studies. r-values assess the False Discovery Rate (FDR) of repilcability
claims acro... |
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