content large_stringlengths 0 6.46M | path large_stringlengths 3 331 | license_type large_stringclasses 2
values | repo_name large_stringlengths 5 125 | language large_stringclasses 1
value | is_vendor bool 2
classes | is_generated bool 2
classes | length_bytes int64 4 6.46M | extension large_stringclasses 75
values | text stringlengths 0 6.46M |
|---|---|---|---|---|---|---|---|---|---|
## simulation rules
set.seed(13053312)
lambda <- 0.2
n <- 40
sim <- 1000
## simulating
sim_test <- matrix(data=rexp(n * sim, lambda), sim)
sim_test_Means <- apply(sim_test, 1, mean)
## range & histogram
range(sim_test_Means)
hist(sim_test_Means , breaks=40 , col="lightblue", border=F , main="Rexp mean distribution", ... | /R06 - Statistical inference/SI_CP.R | no_license | dasmey/Portfolio | R | false | false | 1,191 | r | ## simulation rules
set.seed(13053312)
lambda <- 0.2
n <- 40
sim <- 1000
## simulating
sim_test <- matrix(data=rexp(n * sim, lambda), sim)
sim_test_Means <- apply(sim_test, 1, mean)
## range & histogram
range(sim_test_Means)
hist(sim_test_Means , breaks=40 , col="lightblue", border=F , main="Rexp mean distribution", ... |
#' Generate theoretical GC content distributions
#'
#' This function generates random simulated reads from
#' either provided \code{seqs} (best for RNA-seq)
#' or from a genome (best for DNA-seq). The GC content
#' of these reads is then tabulated to produce a distribution
#' file which can be read by MultiQC to be dis... | /R/core.R | permissive | jnpaulson/fastqcTheoreticalGC | R | false | false | 4,071 | r | #' Generate theoretical GC content distributions
#'
#' This function generates random simulated reads from
#' either provided \code{seqs} (best for RNA-seq)
#' or from a genome (best for DNA-seq). The GC content
#' of these reads is then tabulated to produce a distribution
#' file which can be read by MultiQC to be dis... |
workDir <- "d:/Repos/Cloud4YourData/Demos/4DevKatowice2018/MLRevoscale/Data/Revoscale/"
outPath <- paste0(workDir,"wines.xdf")
sqlConnString <- "Driver=SQL Server; server=.; database=RevoScaleDb; Trusted_Connection = True;"
sqlCC <- RxInSqlServer(connectionString = sqlConnString, numTasks = 1)
sqlQuery <-"SELECT Facid... | /4DevKatowice2018/MLRevoscale/RevoscaleR/Script.R | no_license | beatajaworska/CommunityEvents | R | false | false | 3,606 | r | workDir <- "d:/Repos/Cloud4YourData/Demos/4DevKatowice2018/MLRevoscale/Data/Revoscale/"
outPath <- paste0(workDir,"wines.xdf")
sqlConnString <- "Driver=SQL Server; server=.; database=RevoScaleDb; Trusted_Connection = True;"
sqlCC <- RxInSqlServer(connectionString = sqlConnString, numTasks = 1)
sqlQuery <-"SELECT Facid... |
\name{MCEM}
\alias{MCEM}
\title{Monte Carlo EM algorithm
}
\description{
Use: Computes the MLEs of the Gaussian copula model using the Monte Carlo EM algorithm
}
\usage{
MCEM(obs.data, Monte_Carlo_samples, p, q, initial, num_iterations,
prec=0.01, marginal_dist="negbin",
optim_method... | /man/MCEM.Rd | no_license | hlennon/copulaIVTS | R | false | false | 2,612 | rd | \name{MCEM}
\alias{MCEM}
\title{Monte Carlo EM algorithm
}
\description{
Use: Computes the MLEs of the Gaussian copula model using the Monte Carlo EM algorithm
}
\usage{
MCEM(obs.data, Monte_Carlo_samples, p, q, initial, num_iterations,
prec=0.01, marginal_dist="negbin",
optim_method... |
setwd("~/Documents/Coursera/ExplorData2/ExData_Plotting1")
# Download the file and read it in
url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
filename <- "household.zip"
if(!file.exists("household")) {
download.file(url, filename, method="curl")
file <- unzip("hou... | /plot3.R | no_license | tinaowenmark/ExData_Plotting1 | R | false | false | 1,786 | r |
setwd("~/Documents/Coursera/ExplorData2/ExData_Plotting1")
# Download the file and read it in
url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
filename <- "household.zip"
if(!file.exists("household")) {
download.file(url, filename, method="curl")
file <- unzip("hou... |
# lineup analysis to complement cluster model
library(tidyverse)
library(magrittr)
library(reshape2)
library(lme4)
library(lmerTest)
# get libraries required for bbplot
pacman::p_load('dplyr', 'tidyr', 'gapminder',
'ggplot2', 'ggalt',
'forcats', 'R.utils', 'png',
'grid',... | /Data Modeling/NBA_lineup_model.R | no_license | dhutexas/nba_stats | R | false | false | 9,300 | r | # lineup analysis to complement cluster model
library(tidyverse)
library(magrittr)
library(reshape2)
library(lme4)
library(lmerTest)
# get libraries required for bbplot
pacman::p_load('dplyr', 'tidyr', 'gapminder',
'ggplot2', 'ggalt',
'forcats', 'R.utils', 'png',
'grid',... |
\name{floyd}
\alias{floyd}
\title{Find Shortest Paths Between All Nodes in a Graph}
\description{
The \code{floyd} function finds all shortest paths in a graph using Floyd's algorithm.
}
\usage{
floyd(data)
}
\arguments{
\item{data}{matrix or distance object}
}
\value{
\code{floyd} returns a matrix with... | /man/floyd.Rd | no_license | Dev-RDV/KODAMA | R | false | false | 818 | rd | \name{floyd}
\alias{floyd}
\title{Find Shortest Paths Between All Nodes in a Graph}
\description{
The \code{floyd} function finds all shortest paths in a graph using Floyd's algorithm.
}
\usage{
floyd(data)
}
\arguments{
\item{data}{matrix or distance object}
}
\value{
\code{floyd} returns a matrix with... |
context("Testing azureSMR Blob commands")
test_that("No category", {
blobObject <- list(a = "1", b = "2")
blobName <- "testBlob"
resourceGroup = "asrQuantProduction"
containerName = "testdata"
storageAccount = "asrquantstorage"
verbose <- FALSE
sc <- createAzureContext(tenantID = Sys.getenv("azureTena... | /tests/testthat/test-AzureSMRBlob.R | no_license | CharlesCara/AzureSMRLite | R | false | false | 2,479 | r |
context("Testing azureSMR Blob commands")
test_that("No category", {
blobObject <- list(a = "1", b = "2")
blobName <- "testBlob"
resourceGroup = "asrQuantProduction"
containerName = "testdata"
storageAccount = "asrquantstorage"
verbose <- FALSE
sc <- createAzureContext(tenantID = Sys.getenv("azureTena... |
library(testthat)
library(devtools)
library(Reg)
test_package("Reg")
| /tests/testthat.R | permissive | parismita/Reg | R | false | false | 71 | r | library(testthat)
library(devtools)
library(Reg)
test_package("Reg")
|
library(shiny)
library(shinyAce)
library(tidyverse)
library(ggplot2)
library(DT)
library(dplyr)
shinyUI(fluidPage(
#titlePanel("RStudio shiny app for communicating a data science process."),
navbarPage("RStudio Shiny App",
tabPanel("App",
navlistPanel(
... | /ui.R | permissive | srdjaner/Shiny-app | R | false | false | 16,891 | r | library(shiny)
library(shinyAce)
library(tidyverse)
library(ggplot2)
library(DT)
library(dplyr)
shinyUI(fluidPage(
#titlePanel("RStudio shiny app for communicating a data science process."),
navbarPage("RStudio Shiny App",
tabPanel("App",
navlistPanel(
... |
\name{O.mykiss}
\alias{O.mykiss}
\docType{data}
\title{Test data from a 21 day fish test}
\description{
Test data from a 21 day fish test following the guidelines OECD GL204,
using the test organism Rainbow trout \emph{Oncorhynchus mykiss}.
}
\usage{data(O.mykiss)}
\format{
A data frame wit... | /man/O.mykiss.Rd | no_license | dedream/nlrwr | R | false | false | 864 | rd | \name{O.mykiss}
\alias{O.mykiss}
\docType{data}
\title{Test data from a 21 day fish test}
\description{
Test data from a 21 day fish test following the guidelines OECD GL204,
using the test organism Rainbow trout \emph{Oncorhynchus mykiss}.
}
\usage{data(O.mykiss)}
\format{
A data frame wit... |
df.train<-read.csv('D:/R/data sets/titanic.csv')
head(df.train)
#EDA
#helps in visualizing the NA values
install.packages('Amelia')
library(Amelia)
missmap(df.train, main = "Titanic Training Data - Missing Maps", col=c('yellow','black'), legend=FALSE)
#name of map #first colour shows if its missing, 2nd... | /titanic.R | no_license | AnushreeChakraborty/Logistic-Regression | R | false | false | 2,678 | r | df.train<-read.csv('D:/R/data sets/titanic.csv')
head(df.train)
#EDA
#helps in visualizing the NA values
install.packages('Amelia')
library(Amelia)
missmap(df.train, main = "Titanic Training Data - Missing Maps", col=c('yellow','black'), legend=FALSE)
#name of map #first colour shows if its missing, 2nd... |
#==================
#CreateHouseholds.R
#==================
#<doc>
## CreateHouseholds Module
#### September 6, 2018
#
#This module creates a *Household* table in the datastore and populates the table with datasets characterizing simulated households. Each entry represents a simulated household. Household datasets are... | /sources/modules/VESimHouseholds/R/CreateHouseholds.R | permissive | jslason-rsg/BG_OregonDOT-VisionEval | R | false | false | 37,157 | r | #==================
#CreateHouseholds.R
#==================
#<doc>
## CreateHouseholds Module
#### September 6, 2018
#
#This module creates a *Household* table in the datastore and populates the table with datasets characterizing simulated households. Each entry represents a simulated household. Household datasets are... |
############################################################################
#
############################################################################
loadAllDataSets <- function(dataSet, chipType="*", pattern=NULL, ..., rootPath="totalAndFracBData", type=c("fracB", "total", "genotypes", "confidenceScores"), verbo... | /inst/rsp-ex/TCGA,CMTN/R/loadAllDataSets.R | no_license | HenrikBengtsson/aroma.cn.eval | R | false | false | 4,123 | r | ############################################################################
#
############################################################################
loadAllDataSets <- function(dataSet, chipType="*", pattern=NULL, ..., rootPath="totalAndFracBData", type=c("fracB", "total", "genotypes", "confidenceScores"), verbo... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/501.Error-Failure_LimitBased_BASE_All.R
\name{errWD}
\alias{errWD}
\title{Calculates error, long term power and pass/fail criteria for Wald method}
\usage{
errWD(n, alp, phi, f)
}
\arguments{
\item{n}{- Number of trials}
\item{alp}{- Alpha v... | /man/errWD.Rd | no_license | ElsevierSoftwareX/SOFTX-D-16-00020 | R | false | true | 1,578 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/501.Error-Failure_LimitBased_BASE_All.R
\name{errWD}
\alias{errWD}
\title{Calculates error, long term power and pass/fail criteria for Wald method}
\usage{
errWD(n, alp, phi, f)
}
\arguments{
\item{n}{- Number of trials}
\item{alp}{- Alpha v... |
shinyServer(function(input, output) {
Dataset <- reactive({
if (is.null(input$file1)) {return(NULL)}
else{
text <- readLines(input$file1$datapath )
text = str_replace_all(text, "<.*?>", "")
text = text[text !=""]
return(text)
}
})
lang_model = reactive... | /server.R | no_license | aravindmcs1/ISB-TA-Assignment2 | R | false | false | 2,480 | r |
shinyServer(function(input, output) {
Dataset <- reactive({
if (is.null(input$file1)) {return(NULL)}
else{
text <- readLines(input$file1$datapath )
text = str_replace_all(text, "<.*?>", "")
text = text[text !=""]
return(text)
}
})
lang_model = reactive... |
pro <-read.csv("FHVData.csv")
y = as.numeric(pro$Uber)
pareto.chart(y) | /paretoCode.r | no_license | Soma586/Data | R | false | false | 72 | r | pro <-read.csv("FHVData.csv")
y = as.numeric(pro$Uber)
pareto.chart(y) |
#############################################################
## R code to reproduce statistical analysis in the textbook:
## Agresti, Franklin, Klingenberg
## Statistics: The Art & Science of Learning from Data
## 5th Edition, Pearson 2021
## Web: ArtofStat.com
## Copyright: Bernhard Klingenberg
######################... | /Chapter_2/Chp_2_Example_19.R | no_license | artofstat/RCode | R | false | false | 953 | r | #############################################################
## R code to reproduce statistical analysis in the textbook:
## Agresti, Franklin, Klingenberg
## Statistics: The Art & Science of Learning from Data
## 5th Edition, Pearson 2021
## Web: ArtofStat.com
## Copyright: Bernhard Klingenberg
######################... |
context("run_calculations")
test_that("works", {
## make data
data(sim_pu_raster, sim_features)
p1 <-
problem(sim_pu_raster, sim_features) %>%
add_min_set_objective() %>%
add_relative_targets(0.1) %>%
add_binary_decisions() %>%
add_boundary_penalties(3, 0.5)
p2 <-
problem(sim_pu_raster,... | /tests/testthat/test_run_calculations.R | no_license | bbest/prioritizr | R | false | false | 633 | r | context("run_calculations")
test_that("works", {
## make data
data(sim_pu_raster, sim_features)
p1 <-
problem(sim_pu_raster, sim_features) %>%
add_min_set_objective() %>%
add_relative_targets(0.1) %>%
add_binary_decisions() %>%
add_boundary_penalties(3, 0.5)
p2 <-
problem(sim_pu_raster,... |
testlist <- list(n = -1970667520L)
result <- do.call(breakfast:::setBitNumber,testlist)
str(result) | /breakfast/inst/testfiles/setBitNumber/libFuzzer_setBitNumber/setBitNumber_valgrind_files/1609961662-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 99 | r | testlist <- list(n = -1970667520L)
result <- do.call(breakfast:::setBitNumber,testlist)
str(result) |
#' Replace
#'
#' @param session BasexClient instance-ID
#' @param path Path where to store the data
#' @param input Replacement
#'
#' @return A list with two items
#' \itemize{
#' \item {info} {Aditional info}
#' \item {success} {A boolean, indicating if the command was completed successfull}
#' }
#... | /R/Replace.R | no_license | BenEngbers/RBaseX | R | false | false | 1,007 | r | #' Replace
#'
#' @param session BasexClient instance-ID
#' @param path Path where to store the data
#' @param input Replacement
#'
#' @return A list with two items
#' \itemize{
#' \item {info} {Aditional info}
#' \item {success} {A boolean, indicating if the command was completed successfull}
#' }
#... |
library(waterfall)
# Lager et dataframe med to kolonner med scores
set.seed(13435)
x <- data.frame("label"=c("A","B","C","D","E"),"value"=c(5,15,-4,12,2))
x
# Tester Waterfall chart:
waterfallchart(value~label, data=x, col=c(1,2))
| /waterfall chart.R | no_license | MHaneferd/RScripts | R | false | false | 233 | r | library(waterfall)
# Lager et dataframe med to kolonner med scores
set.seed(13435)
x <- data.frame("label"=c("A","B","C","D","E"),"value"=c(5,15,-4,12,2))
x
# Tester Waterfall chart:
waterfallchart(value~label, data=x, col=c(1,2))
|
## Put comments here that give an overall description of what your
# funtion to make the cache matrix
makeCacheMatrix <- function(x = matrix()) {
cacheMatrix <- NULL
setMatrix <- function(y) {
x <<- y
cacheMatrix <<- NULL
}
getMatrix <- function() x
... | /cachematrix.R | no_license | cilidon/ProgrammingAssignment2 | R | false | false | 919 | r | ## Put comments here that give an overall description of what your
# funtion to make the cache matrix
makeCacheMatrix <- function(x = matrix()) {
cacheMatrix <- NULL
setMatrix <- function(y) {
x <<- y
cacheMatrix <<- NULL
}
getMatrix <- function() x
... |
#' RNA-Seq of a TNBC patient
#'
#' A dataset containing RNA-Seq data of two transcriptomes belonging to a triple negative breast
#' cancer (TNBC) patient
#'
#'
#' @format A data frame with 20501 rows and 2 columns:
#' \describe{
#' \item{Tumor_Sample}{RNA-Seq data of a tumor sample}
#' \item{Healthy_Sample}{RNA-S... | /R/data.R | no_license | alfonsosaera/iDEG | R | false | false | 431 | r | #' RNA-Seq of a TNBC patient
#'
#' A dataset containing RNA-Seq data of two transcriptomes belonging to a triple negative breast
#' cancer (TNBC) patient
#'
#'
#' @format A data frame with 20501 rows and 2 columns:
#' \describe{
#' \item{Tumor_Sample}{RNA-Seq data of a tumor sample}
#' \item{Healthy_Sample}{RNA-S... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/response.R
\name{print.response}
\alias{print.response}
\title{Printing Responses}
\usage{
\method{print}{response}(x, ...)
}
\arguments{
\item{x}{Object of class \code{response}.}
\item{\ldots}{Ignored.}
}
\description{
Print a response obj... | /man/print.response.Rd | no_license | waynenilsen/prairie | R | false | true | 436 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/response.R
\name{print.response}
\alias{print.response}
\title{Printing Responses}
\usage{
\method{print}{response}(x, ...)
}
\arguments{
\item{x}{Object of class \code{response}.}
\item{\ldots}{Ignored.}
}
\description{
Print a response obj... |
#' The Amari-alpha Csiszar-function in log-space
#'
#' A Csiszar-function is a member of ` F = { f:R_+ to R : f convex } `.
#'
#' When `self_normalized = TRUE`, the Amari-alpha Csiszar-function is:
#'
#' ```
#' f(u) = { -log(u) + (u - 1)}, alpha = 0
#' { u log(u) - (u - 1)}, alpha = 1
#' { ((u^alph... | /R/vi-functions.R | permissive | jeffreypullin/tfprobability | R | false | false | 24,872 | r | #' The Amari-alpha Csiszar-function in log-space
#'
#' A Csiszar-function is a member of ` F = { f:R_+ to R : f convex } `.
#'
#' When `self_normalized = TRUE`, the Amari-alpha Csiszar-function is:
#'
#' ```
#' f(u) = { -log(u) + (u - 1)}, alpha = 0
#' { u log(u) - (u - 1)}, alpha = 1
#' { ((u^alph... |
# SDC processing - plotting observed data and smoothing curves
# querying of melt-seasons per ez and year
# script version: 2012-01-27
library(sqldf)
library (tseries)
library(timeSeries)
# change settings here --------------------------------------------------
options(warn=-1)
y1 <- 2005 # first year
y2 <- 2012 # l... | /SDC_calc_gapfree.R | no_license | climatepals/R-Scripts | R | false | false | 7,039 | r | # SDC processing - plotting observed data and smoothing curves
# querying of melt-seasons per ez and year
# script version: 2012-01-27
library(sqldf)
library (tseries)
library(timeSeries)
# change settings here --------------------------------------------------
options(warn=-1)
y1 <- 2005 # first year
y2 <- 2012 # l... |
## Load the required libraries
library(dplyr)
# Check if raw_data is loaded, else get the data.
if(!exists("raw_data", mode="function")) source("Assignment_1_Getting_Data.R")
# Arranging the data by date
by_date <- group_by(raw_data, date)
# Calculating total steps for each day
t_s <- summarize(by_date, Total_Steps ... | /Assignment_1a_CodeV2.R | no_license | Sahil-yp/RepData_PeerAssessment1 | R | false | false | 782 | r | ## Load the required libraries
library(dplyr)
# Check if raw_data is loaded, else get the data.
if(!exists("raw_data", mode="function")) source("Assignment_1_Getting_Data.R")
# Arranging the data by date
by_date <- group_by(raw_data, date)
# Calculating total steps for each day
t_s <- summarize(by_date, Total_Steps ... |
library(qtlc)
### Name: s3D
### Title: Internal function used by showtlc3D
### Aliases: s3D
### ** Examples
## Not run:
##D #Internal function.
## End(Not run)
| /data/genthat_extracted_code/qtlc/examples/s3D.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 169 | r | library(qtlc)
### Name: s3D
### Title: Internal function used by showtlc3D
### Aliases: s3D
### ** Examples
## Not run:
##D #Internal function.
## End(Not run)
|
## These functions compute the inverse of a matrix only if it
## has not already been calculated.
## This function creates a special "matrix" object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
set <- function(y) {
x <<- y
m <<- NULL
}
get <- functio... | /cachematrix.R | no_license | Iridella/ProgrammingAssignment2 | R | false | false | 1,147 | r | ## These functions compute the inverse of a matrix only if it
## has not already been calculated.
## This function creates a special "matrix" object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
set <- function(y) {
x <<- y
m <<- NULL
}
get <- functio... |
testlist <- list(G = numeric(0), Rn = numeric(0), atmp = numeric(0), ra = numeric(0), relh = c(1.9433118586544e+185, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), rs = numeric(0), temp = c(-4.18240144581448e-209, 3.13151605919845e-294, 9.29609968145595e+121, -5.24735735928569e-235, ... | /meteor/inst/testfiles/ET0_PenmanMonteith/AFL_ET0_PenmanMonteith/ET0_PenmanMonteith_valgrind_files/1615842267-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 790 | r | testlist <- list(G = numeric(0), Rn = numeric(0), atmp = numeric(0), ra = numeric(0), relh = c(1.9433118586544e+185, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), rs = numeric(0), temp = c(-4.18240144581448e-209, 3.13151605919845e-294, 9.29609968145595e+121, -5.24735735928569e-235, ... |
`%>%` <- magrittr::`%>%`
effects_file = "../data2/gtex/lead_effects_na.tsv"
output_dir = "../data2/gtex/mfactorization/"
effects = readr::read_tsv(effects_file)
dir.create(output_dir, recursive = T)
dplyr::select(effects, variant, molecular_trait_id, ends_with('.beta')) %>%
dplyr::rename_all(function(x){sub(".beta"... | /get_effects.R | permissive | peikovakate/ts_eQTLs | R | false | false | 697 | r | `%>%` <- magrittr::`%>%`
effects_file = "../data2/gtex/lead_effects_na.tsv"
output_dir = "../data2/gtex/mfactorization/"
effects = readr::read_tsv(effects_file)
dir.create(output_dir, recursive = T)
dplyr::select(effects, variant, molecular_trait_id, ends_with('.beta')) %>%
dplyr::rename_all(function(x){sub(".beta"... |
#assumption: input must be of the shape (x, y, z)
#if input is 2d, it can be transformed as (x, y, 1)
relu <- function(stacks)
{
shape <- dim(stacks)
for(z in seq(shape[3])){
for (y in seq(shape[2]))
{
for (x in seq(shape[1]))
stacks[x, y, z] <- max(stacks[x, y, z], 0)
}
}
#re... | /lab-assignment/source-code/relu.R | no_license | tintinrevient/machine-learning-for-human-vision-and-language | R | false | false | 457 | r | #assumption: input must be of the shape (x, y, z)
#if input is 2d, it can be transformed as (x, y, 1)
relu <- function(stacks)
{
shape <- dim(stacks)
for(z in seq(shape[3])){
for (y in seq(shape[2]))
{
for (x in seq(shape[1]))
stacks[x, y, z] <- max(stacks[x, y, z], 0)
}
}
#re... |
library(shiny)
library(shinyFiles)
shinyUI(pageWithSidebar(
headerPanel(
"Selections with shinyFiles",
"shinyFiles example"
),
sidebarPanel(
img(src = "logo.png", style = "float: left; width: 120px; margin-right: 10px; margin-top: 5px"),
tags$p("The following buttons will expose the users R insta... | /inst/example/ui.R | no_license | rpodcast/shinyFiles | R | false | false | 3,755 | r | library(shiny)
library(shinyFiles)
shinyUI(pageWithSidebar(
headerPanel(
"Selections with shinyFiles",
"shinyFiles example"
),
sidebarPanel(
img(src = "logo.png", style = "float: left; width: 120px; margin-right: 10px; margin-top: 5px"),
tags$p("The following buttons will expose the users R insta... |
getwd()
p='C:/Users/Admin/Downloads/blogfeedback'
setwd(p)
list.files()
list.dirs()
library(data.table)
blogData_train <- read_csv('C:/Users/Admin/Downloads/blogfeedback/blogData_train.csv')
View(blogData_train)
library(ISLR)
train_sg <- read.csv("blogfeedback/train_sg.csv")
test_sg <- read.csv("blogfee... | /14.R | no_license | drj819/assgn14.1 | R | false | false | 885 | r |
getwd()
p='C:/Users/Admin/Downloads/blogfeedback'
setwd(p)
list.files()
list.dirs()
library(data.table)
blogData_train <- read_csv('C:/Users/Admin/Downloads/blogfeedback/blogData_train.csv')
View(blogData_train)
library(ISLR)
train_sg <- read.csv("blogfeedback/train_sg.csv")
test_sg <- read.csv("blogfee... |
# Data mining and text mining - Politecnico di Milano
# Alessandro Baldassari
# Data Mining competition - BIP data
# Loading dataset
train <- read.csv("~/Git/data mining/dataset_polimi.csv")
# Product type String -> boolean
train$Categoria_prodotto <- as.character(train$Categoria_prodotto)
train$Prodotto_1 <- "0"
tra... | /Data preparation/data_manipulation.r | no_license | AChiolini/Data-Mining-BiP | R | false | false | 2,213 | r | # Data mining and text mining - Politecnico di Milano
# Alessandro Baldassari
# Data Mining competition - BIP data
# Loading dataset
train <- read.csv("~/Git/data mining/dataset_polimi.csv")
# Product type String -> boolean
train$Categoria_prodotto <- as.character(train$Categoria_prodotto)
train$Prodotto_1 <- "0"
tra... |
\name{dlm}
\alias{dlm}
\alias{as.dlm}
\alias{is.dlm}
\title{dlm objects}
\description{
The function \code{dlm} is used to create Dynamic Linear Model objects.
\code{as.dlm} and \code{is.dlm} coerce an object to a Dynamic Linear
Model object and test whether an object is a Dynamic Linear Model.
}
\usage{
dlm(...)... | /man/dlm.Rd | no_license | pchristi99/dlm | R | false | false | 2,504 | rd | \name{dlm}
\alias{dlm}
\alias{as.dlm}
\alias{is.dlm}
\title{dlm objects}
\description{
The function \code{dlm} is used to create Dynamic Linear Model objects.
\code{as.dlm} and \code{is.dlm} coerce an object to a Dynamic Linear
Model object and test whether an object is a Dynamic Linear Model.
}
\usage{
dlm(...)... |
# Examine the univariate data ---------------------------------------------
#univariate data = samples of one variable
#univariate data analysis isn't concerned with the 'why'. It is just to decribe the data as it is.
#discrete variables vs continuous variables
#discrete = an eample is the level of education. It has a ... | /ExplorativeDataAnalysis/EDA_univariant_analysis.R | no_license | MarcusGrund/R_Foundations | R | false | false | 2,269 | r | # Examine the univariate data ---------------------------------------------
#univariate data = samples of one variable
#univariate data analysis isn't concerned with the 'why'. It is just to decribe the data as it is.
#discrete variables vs continuous variables
#discrete = an eample is the level of education. It has a ... |
context("regr.catboost")
test_that("autotest", {
learner = LearnerRegrCatboost$new()
expect_learner(learner)
result = run_autotest(learner)
expect_true(result, info = result$error)
})
| /tests/testthat/test_regr.catboost.R | no_license | mlr3learners/mlr3learners.catboost | R | false | false | 193 | r | context("regr.catboost")
test_that("autotest", {
learner = LearnerRegrCatboost$new()
expect_learner(learner)
result = run_autotest(learner)
expect_true(result, info = result$error)
})
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/genomics_functions.R
\name{variantsets.get}
\alias{variantsets.get}
\title{Gets a variant set by ID.For the definitions of variant sets and other genomics resources, see[Fundamentals of GoogleGenomics](https://cloud.google.com/genomics/fundam... | /googlegenomicsv1.auto/man/variantsets.get.Rd | permissive | GVersteeg/autoGoogleAPI | R | false | true | 1,126 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/genomics_functions.R
\name{variantsets.get}
\alias{variantsets.get}
\title{Gets a variant set by ID.For the definitions of variant sets and other genomics resources, see[Fundamentals of GoogleGenomics](https://cloud.google.com/genomics/fundam... |
# UserDefnFunction
# Uses Prostrate Data
# scale()
#
# Author: PatriciaHoffman
###############################################################################
rm(list=ls())
?source
##################################################
# User Defined Function - roll die
###################... | /week1/RCode/UserDefnFunction.R | no_license | saurabhmadaan/ML_UCSC | R | false | false | 5,326 | r |
# UserDefnFunction
# Uses Prostrate Data
# scale()
#
# Author: PatriciaHoffman
###############################################################################
rm(list=ls())
?source
##################################################
# User Defined Function - roll die
###################... |
## app.R ##
library(shinydashboard)
library(shinydashboardPlus)
library(shiny)
library(tidyverse)
library(readxl)
library(ggthemes)
library(ggrepel)
library(shinyWidgets)
library(plotly)
library(shinycssloaders)
library(dashboardthemes)
library(RCzechia)
library(leaflet)
library(sf)
library(RJSONIO)
library(deSolve)
... | /app.R | no_license | 3p1463k/nCov2019CZ | R | false | false | 13,763 | r | ## app.R ##
library(shinydashboard)
library(shinydashboardPlus)
library(shiny)
library(tidyverse)
library(readxl)
library(ggthemes)
library(ggrepel)
library(shinyWidgets)
library(plotly)
library(shinycssloaders)
library(dashboardthemes)
library(RCzechia)
library(leaflet)
library(sf)
library(RJSONIO)
library(deSolve)
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/a3_power.R
\name{emp_power}
\alias{emp_power}
\title{Empirical power of a t-test}
\usage{
emp_power(n, mu, mu0, sd, alpha = 0.05, R = 1000, type = c("one_sample",
"two_sample"), ...)
}
\arguments{
\item{n}{numeric. sample size}
\item{mu}{m... | /man/emp_power.Rd | permissive | JasperHG90/meerkat | R | false | true | 2,982 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/a3_power.R
\name{emp_power}
\alias{emp_power}
\title{Empirical power of a t-test}
\usage{
emp_power(n, mu, mu0, sd, alpha = 0.05, R = 1000, type = c("one_sample",
"two_sample"), ...)
}
\arguments{
\item{n}{numeric. sample size}
\item{mu}{m... |
library(h2o)
h2o.init(nthreads=-1)
dx <- h2o.importFile("wk09/lect/data/airline100K.csv")
dx_split <- h2o.splitFrame(dx, ratios = c(0.6,0.2), seed = 123)
dx_train <- dx_split[[1]]
dx_valid <- dx_split[[2]]
dx_test <- dx_split[[3]]
Xnames <- names(dx_train)[which(names(dx_train)!="dep_delayed_15min")]
system.t... | /wk11/lect/2-NN/h2o.R | no_license | paljenczy/teach-ML-CEU-master-bizanalytics | R | false | false | 8,827 | r |
library(h2o)
h2o.init(nthreads=-1)
dx <- h2o.importFile("wk09/lect/data/airline100K.csv")
dx_split <- h2o.splitFrame(dx, ratios = c(0.6,0.2), seed = 123)
dx_train <- dx_split[[1]]
dx_valid <- dx_split[[2]]
dx_test <- dx_split[[3]]
Xnames <- names(dx_train)[which(names(dx_train)!="dep_delayed_15min")]
system.t... |
#!/usr/bin/env Rscript
# Copyright (c) 2017 Michael Roach (Australian Wine Research Institute)
#
# 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 limita... | /dx_applets/purge_haplotigs/purge_haplotigs_contigcov_and_purge/resources/home/dnanexus/dot_plot.Rscript | permissive | VGP/vgp-assembly | R | false | false | 4,446 | rscript | #!/usr/bin/env Rscript
# Copyright (c) 2017 Michael Roach (Australian Wine Research Institute)
#
# 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 limita... |
path2data <- "C:\\Data\\My Documents\\Courses\\Data Science\\Exploratory Data Analysis\\Project\\exdata-data-household_power_consumption\\household_power_consumption.txt"
## Read the names of the variables
datanames <- read.table(path2data, sep=";", nrows=1, colClasses="character")
## Read the data and format
data <... | /plot3.R | no_license | sashalyulko/ExData_Plotting1 | R | false | false | 1,139 | r | path2data <- "C:\\Data\\My Documents\\Courses\\Data Science\\Exploratory Data Analysis\\Project\\exdata-data-household_power_consumption\\household_power_consumption.txt"
## Read the names of the variables
datanames <- read.table(path2data, sep=";", nrows=1, colClasses="character")
## Read the data and format
data <... |
cycle_to_lookup_year <- function(cycle) {
return(switch(cycle,
"1999-2000" = "A 99-00",
"2001-2002" = "A 01-02",
"2003-2004" = "A 03-04",
"2005-2006" = "A 05-06",
"2007-2008" = "A 07-08",
"2009-2010" = "A 09-10",
... | /R/lookup_table.R | permissive | SilentSpringInstitute/RNHANES | R | false | false | 722 | r | cycle_to_lookup_year <- function(cycle) {
return(switch(cycle,
"1999-2000" = "A 99-00",
"2001-2002" = "A 01-02",
"2003-2004" = "A 03-04",
"2005-2006" = "A 05-06",
"2007-2008" = "A 07-08",
"2009-2010" = "A 09-10",
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/simves.R
\name{sim.ves}
\alias{sim.ves}
\title{Simulate Vector Exponential Smoothing}
\usage{
sim.ves(model = "ANN", obs = 10, nsim = 1, nSeries = 2, frequency = 1,
persistence = NULL, phi = 1, transition = NULL, initial = NULL,
initialSe... | /man/sim.ves.Rd | no_license | lixixibj/smooth | R | false | true | 6,671 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/simves.R
\name{sim.ves}
\alias{sim.ves}
\title{Simulate Vector Exponential Smoothing}
\usage{
sim.ves(model = "ANN", obs = 10, nsim = 1, nSeries = 2, frequency = 1,
persistence = NULL, phi = 1, transition = NULL, initial = NULL,
initialSe... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/downloaders.R
\name{wget}
\alias{wget}
\title{wget}
\usage{
wget(
input_url,
output_path,
background = T,
force_overwrite = F,
quiet = F,
show_progress = T,
continue = T,
check_certificates = F,
conda_env = "echoR"
)
}
\desc... | /man/wget.Rd | permissive | UKDRI/echolocatoR | R | false | true | 472 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/downloaders.R
\name{wget}
\alias{wget}
\title{wget}
\usage{
wget(
input_url,
output_path,
background = T,
force_overwrite = F,
quiet = F,
show_progress = T,
continue = T,
check_certificates = F,
conda_env = "echoR"
)
}
\desc... |
## EXData - Project 1 - Plot 4
powerdata <- read.table("household_power_consumption.txt", header=TRUE, sep=";", na.strings="?", stringsAsFactors = FALSE)
power <- subset(powerdata, Date == "1/2/2007" | Date == "2/2/2007")
power$ts <- paste(power$Date, power$Time)
power$ts <- strptime(power$ts, format = "%d/%m/%Y %H:%M... | /plot4.R | no_license | equan/ExData_Plotting1 | R | false | false | 1,220 | r | ## EXData - Project 1 - Plot 4
powerdata <- read.table("household_power_consumption.txt", header=TRUE, sep=";", na.strings="?", stringsAsFactors = FALSE)
power <- subset(powerdata, Date == "1/2/2007" | Date == "2/2/2007")
power$ts <- paste(power$Date, power$Time)
power$ts <- strptime(power$ts, format = "%d/%m/%Y %H:%M... |
#' @title Topic Modelling in Semantic Embedding Spaces
#' @description ETM is a generative topic model combining traditional topic models (LDA) with word embeddings (word2vec). \cr
#' \itemize{
#' \item{It models each word with a categorical distribution whose natural parameter is the inner product between
#' a word e... | /R/ETM.R | permissive | mstei4176/ETM | R | false | false | 27,311 | r |
#' @title Topic Modelling in Semantic Embedding Spaces
#' @description ETM is a generative topic model combining traditional topic models (LDA) with word embeddings (word2vec). \cr
#' \itemize{
#' \item{It models each word with a categorical distribution whose natural parameter is the inner product between
#' a word e... |
countries <- read_csv("data/countries.csv")
indicators <- read_csv("data/indicators.csv")
get_wdi_indicator <- function(country, indicator) {
Sys.sleep(3)
WDI(
country = country,
indicator = c("value" = indicator)
) %>%
as_tibble()
}
get_indicator_name <- function(selected_indicator) {
indicator... | /09_03/data-processing.R | no_license | dmancilla85/r-shiny-essential-training | R | false | false | 531 | r |
countries <- read_csv("data/countries.csv")
indicators <- read_csv("data/indicators.csv")
get_wdi_indicator <- function(country, indicator) {
Sys.sleep(3)
WDI(
country = country,
indicator = c("value" = indicator)
) %>%
as_tibble()
}
get_indicator_name <- function(selected_indicator) {
indicator... |
#' Get Raindrop Trace
#' @description Uses a raindrop trace web service to trace the
#' nhdplus digital elevation model to the nearest downslop flowline.
#' @param point sfc POINT including crs as created by:
#' \code{sf::st_sfc(sf::st_point(.. ,..), crs)}
#' @param direction character \code{"up"}, \code{"down"}, or \c... | /R/get_oaproc.R | permissive | mikejohnson51/nhdplusTools | R | false | false | 14,710 | r | #' Get Raindrop Trace
#' @description Uses a raindrop trace web service to trace the
#' nhdplus digital elevation model to the nearest downslop flowline.
#' @param point sfc POINT including crs as created by:
#' \code{sf::st_sfc(sf::st_point(.. ,..), crs)}
#' @param direction character \code{"up"}, \code{"down"}, or \c... |
#######################################################################
# #
# Package: onemap #
# #
# File: draw.map.R ... | /onemap/R/draw.map.R | no_license | ingted/R-Examples | R | false | false | 3,761 | r | #######################################################################
# #
# Package: onemap #
# #
# File: draw.map.R ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/process_data.R
\name{create_anno_region}
\alias{create_anno_region}
\title{Create annotation regions}
\usage{
create_anno_region(
anno,
chrom_size = NULL,
is_centre = FALSE,
is_window = TRUE,
upstream = -5000,
downstream = 5000
)
... | /man/create_anno_region.Rd | permissive | andreaskapou/BPRMeth | R | false | true | 2,478 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/process_data.R
\name{create_anno_region}
\alias{create_anno_region}
\title{Create annotation regions}
\usage{
create_anno_region(
anno,
chrom_size = NULL,
is_centre = FALSE,
is_window = TRUE,
upstream = -5000,
downstream = 5000
)
... |
library("rjson")
data <- fromJSON(file="data.json")
new_dataa = as.data.frame(data)
##new_dataa[1]
##new_dataa[8160]
## before sorting
## first value new_dataa[1]
## last value new_dataa[8160]
pickle = new_dataa[, order(names(new_dataa))]
## after sorting
## first value pickle[3]
## last value pickle[8162]
enter_in... | /rough work/single_cur_month.r | no_license | sanket9006/2020-interns | R | false | false | 948 | r | library("rjson")
data <- fromJSON(file="data.json")
new_dataa = as.data.frame(data)
##new_dataa[1]
##new_dataa[8160]
## before sorting
## first value new_dataa[1]
## last value new_dataa[8160]
pickle = new_dataa[, order(names(new_dataa))]
## after sorting
## first value pickle[3]
## last value pickle[8162]
enter_in... |
library(R.matlab)
subjid_df <- read.csv("/data/jux/BBL/projects/pncSingleFuncParcel/Replication/data/pncSingleFuncParcel_n693_SubjectsIDs.csv");
#########################################
### 2. Extrating behavior information ###
#########################################
demo <- subjid_df;
# Demographics
Demographi... | /Step_1st_PrepareData/Step_2nd_ExtractBehavior.R | no_license | guoweiwuorgin/pncSingleFuncParcel | R | false | false | 1,709 | r |
library(R.matlab)
subjid_df <- read.csv("/data/jux/BBL/projects/pncSingleFuncParcel/Replication/data/pncSingleFuncParcel_n693_SubjectsIDs.csv");
#########################################
### 2. Extrating behavior information ###
#########################################
demo <- subjid_df;
# Demographics
Demographi... |
setwd("C:\\Users\\Mershack\\Documents\\NetbeansProjects\\GitHub_projects\\d3graphevaluation\\build\\web\\studies\\study5\\data")
sink("rscript-friedman.txt")
accuracy1 = read.csv("AccuracyResults1.txt")
accuracy2 = read.csv("AccuracyResults2.txt")
Acc_neighbor_one_step_edgesize2= c(accuracy1[,1])
Acc_neighbor_one_step_... | /build/web/studies/study4/data/rscript-friedman.R | no_license | mershack/graphunit | R | false | false | 1,543 | r | setwd("C:\\Users\\Mershack\\Documents\\NetbeansProjects\\GitHub_projects\\d3graphevaluation\\build\\web\\studies\\study5\\data")
sink("rscript-friedman.txt")
accuracy1 = read.csv("AccuracyResults1.txt")
accuracy2 = read.csv("AccuracyResults2.txt")
Acc_neighbor_one_step_edgesize2= c(accuracy1[,1])
Acc_neighbor_one_step_... |
## the script is used for creating a tidy dataset based on
## data collected from the accelerometers from the Samsung Galaxy S smartphone
library(reshape2)
library(plyr)
root_dir <- "UCI HAR Dataset"
## import label and feature
features <- read.table(paste(root_dir,"features.txt",sep="/"), stringsAsFactors=F)
activit... | /run_analysis.R | no_license | AndyLiu0429/GCDAssignment | R | false | false | 1,739 | r | ## the script is used for creating a tidy dataset based on
## data collected from the accelerometers from the Samsung Galaxy S smartphone
library(reshape2)
library(plyr)
root_dir <- "UCI HAR Dataset"
## import label and feature
features <- read.table(paste(root_dir,"features.txt",sep="/"), stringsAsFactors=F)
activit... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pareto.R
\name{dparteo}
\alias{dparteo}
\title{The probability density function of the pareto distribution.}
\usage{
dparteo(x, alpha, x_m, log.p = FALSE)
}
\arguments{
\item{x}{the point where the pdf to be evaluated}
\item{alpha}{the shape... | /man/dparteo.Rd | no_license | petershan1119/paretopractice | R | false | true | 690 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pareto.R
\name{dparteo}
\alias{dparteo}
\title{The probability density function of the pareto distribution.}
\usage{
dparteo(x, alpha, x_m, log.p = FALSE)
}
\arguments{
\item{x}{the point where the pdf to be evaluated}
\item{alpha}{the shape... |
### Get dates from the uncleaned data (NAs not removed)
head(UNMcaptures)
UNMcaptures$date <- as.Date(gsub(" ", "", UNMcaptures$Date),format="%m/%d/%Y")
sort(unique(UNMcaptures$date))
Z2.dates <- sort(unique(UNMcaptures$date[which(UNMcaptures$site=="Zuni"&UNMcaptures$web==2)]))
time.int <- diff(Z2.dates)
first.dates ... | /Old Code/Z2CaptureHistories.R | no_license | angieluis/BayesianMarkRecapSNV | R | false | false | 2,611 | r | ### Get dates from the uncleaned data (NAs not removed)
head(UNMcaptures)
UNMcaptures$date <- as.Date(gsub(" ", "", UNMcaptures$Date),format="%m/%d/%Y")
sort(unique(UNMcaptures$date))
Z2.dates <- sort(unique(UNMcaptures$date[which(UNMcaptures$site=="Zuni"&UNMcaptures$web==2)]))
time.int <- diff(Z2.dates)
first.dates ... |
#Hands_On Book ----
# NOTE: To comment out text use Cmd + Shift + C
# To run ALL code CMD + SHIFT + RETURN
# To run current selection or code on line CMD + RETURN
1 + 1
#2
#
10:15
#10 11 12 13 14 15
typeof(10:15)
#integer
a <- 1
a
#1 a is an 'object'
typeof(a)
a * 3
#3
typeof(a)
#"double" meaning double length s... | /Chap1_The_Basics.R | no_license | kendogprior/R_practice | R | false | false | 2,055 | r | #Hands_On Book ----
# NOTE: To comment out text use Cmd + Shift + C
# To run ALL code CMD + SHIFT + RETURN
# To run current selection or code on line CMD + RETURN
1 + 1
#2
#
10:15
#10 11 12 13 14 15
typeof(10:15)
#integer
a <- 1
a
#1 a is an 'object'
typeof(a)
a * 3
#3
typeof(a)
#"double" meaning double length s... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/app.R
\name{shinyapp}
\alias{shinyapp}
\title{Class to manage a shiny app and a phantom.js headless browser}
\description{
Class to manage a shiny app and a phantom.js headless browser
}
\section{Usage}{
\preformatted{app <- shinyapp$new(pat... | /man/shinyapp.Rd | permissive | carlganz/shinytest | R | false | true | 5,971 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/app.R
\name{shinyapp}
\alias{shinyapp}
\title{Class to manage a shiny app and a phantom.js headless browser}
\description{
Class to manage a shiny app and a phantom.js headless browser
}
\section{Usage}{
\preformatted{app <- shinyapp$new(pat... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{misc_uk}
\alias{misc_uk}
\title{misc_uk}
\format{
An object of class \code{spec_tbl_df} (inherits from \code{tbl_df}, \code{tbl}, \code{data.frame}) with 214 rows and 10 columns.
}
\usage{
misc_uk
}
\description{
m... | /man/misc_uk.Rd | permissive | sjbeckett/localcovid19now | R | false | true | 348 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{misc_uk}
\alias{misc_uk}
\title{misc_uk}
\format{
An object of class \code{spec_tbl_df} (inherits from \code{tbl_df}, \code{tbl}, \code{data.frame}) with 214 rows and 10 columns.
}
\usage{
misc_uk
}
\description{
m... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/prometheusservice_operations.R
\name{prometheusservice_describe_rule_groups_namespace}
\alias{prometheusservice_describe_rule_groups_namespace}
\title{Describe a rule groups namespace}
\usage{
prometheusservice_describe_rule_groups_namespace(... | /cran/paws.management/man/prometheusservice_describe_rule_groups_namespace.Rd | permissive | paws-r/paws | R | false | true | 661 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/prometheusservice_operations.R
\name{prometheusservice_describe_rule_groups_namespace}
\alias{prometheusservice_describe_rule_groups_namespace}
\title{Describe a rule groups namespace}
\usage{
prometheusservice_describe_rule_groups_namespace(... |
#
# Assignment for Exploratory Data Analysis
#
#
## 00. Libraries ----
library(dplyr)
library(tidyr)
library(ggplot2)
## 00. Import data if it exists ----
if(file.exists("data/Source_Classification_Code.rds")){
d1 <- readRDS(file="data/Source_Classification_Code.rds")
}
if(file.exists("data/summarySCC_PM25.rds... | /Plot1.R | no_license | mnoro/EDA_Project | R | false | false | 1,015 | r | #
# Assignment for Exploratory Data Analysis
#
#
## 00. Libraries ----
library(dplyr)
library(tidyr)
library(ggplot2)
## 00. Import data if it exists ----
if(file.exists("data/Source_Classification_Code.rds")){
d1 <- readRDS(file="data/Source_Classification_Code.rds")
}
if(file.exists("data/summarySCC_PM25.rds... |
##########################################
# #
# ADDING UP STEM QUALIFICATIONS #
# ERIKA JACOBS #
# PENNSYLVANIA STATE UNIVERSITY #
# 2018 #
# #
##################... | /Jacobs Capstone R Script.R | no_license | ErikaJacobs/Common-Core-Intervention-Analysis | R | false | false | 7,128 | r | ##########################################
# #
# ADDING UP STEM QUALIFICATIONS #
# ERIKA JACOBS #
# PENNSYLVANIA STATE UNIVERSITY #
# 2018 #
# #
##################... |
## TODO: pass ... to all the things
## TODO: totally rewrite in temrs of tidyverse functions
#' Substantive effects via simulation
#' @param m a model.
#' @param x a population within which to simulate effects. Default \code{model.frame(m)} (the original population).
#' @param Z a named ist of two or more contrasting ... | /R/gilez.R | no_license | deepfriar/gilez | R | false | false | 3,496 | r | ## TODO: pass ... to all the things
## TODO: totally rewrite in temrs of tidyverse functions
#' Substantive effects via simulation
#' @param m a model.
#' @param x a population within which to simulate effects. Default \code{model.frame(m)} (the original population).
#' @param Z a named ist of two or more contrasting ... |
c DCNF-Autarky [version 0.0.1].
c Copyright (c) 2018-2019 Swansea University.
c
c Input Clause Count: 23182
c Performing E1-Autarky iteration.
c Remaining clauses count after E-Reduction: 23182
c
c Input Parameter (command line, file):
c input filename QBFLIB/Amendola-Ricca-Truszczynski/selection-hard/ctrl.e#1.a#... | /code/dcnf-ankit-optimized/Results/QBFLIB-2018/E1/Experiments/Amendola-Ricca-Truszczynski/selection-hard/ctrl.e#1.a#3.E#138.A#48.c#.w#7.s#35.asp/ctrl.e#1.a#3.E#138.A#48.c#.w#7.s#35.asp.R | no_license | arey0pushpa/dcnf-autarky | R | false | false | 732 | r | c DCNF-Autarky [version 0.0.1].
c Copyright (c) 2018-2019 Swansea University.
c
c Input Clause Count: 23182
c Performing E1-Autarky iteration.
c Remaining clauses count after E-Reduction: 23182
c
c Input Parameter (command line, file):
c input filename QBFLIB/Amendola-Ricca-Truszczynski/selection-hard/ctrl.e#1.a#... |
#Creates a caregiver_ed score, the average educational attainment of the child's caregivers
library(dplyr)
#Load in data
questionnaire <- read.delim(dir("data_categories/questionnaire/",
full.names=T, pattern="^questionnaire_20"),header=TRUE, sep="\t")
#Create dataframe
caregiver_ed ... | /caregiver_ed.R | no_license | hddsilva/participant_subsets | R | false | false | 1,325 | r | #Creates a caregiver_ed score, the average educational attainment of the child's caregivers
library(dplyr)
#Load in data
questionnaire <- read.delim(dir("data_categories/questionnaire/",
full.names=T, pattern="^questionnaire_20"),header=TRUE, sep="\t")
#Create dataframe
caregiver_ed ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gets.R
\name{getUserPlayslists}
\alias{getUserPlayslists}
\title{Retuns a data frame of the users playlists.}
\usage{
getUserPlayslists(userID)
}
\arguments{
\item{userID}{The wanted user id as a string}
}
\value{
Returns a dataframe that con... | /man/getUserPlayslists.Rd | no_license | topiaskarjalainen/SpotR | R | false | true | 490 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gets.R
\name{getUserPlayslists}
\alias{getUserPlayslists}
\title{Retuns a data frame of the users playlists.}
\usage{
getUserPlayslists(userID)
}
\arguments{
\item{userID}{The wanted user id as a string}
}
\value{
Returns a dataframe that con... |
# as_range_spec() ----
test_that("as_range_spec() rejects hopeless input", {
expect_error(as_range_spec(3), "Can't make a range")
})
test_that("as_range_spec() can deal with nothingness", {
spec <- as_range_spec(NULL)
expect_true(all(map_lgl(spec, ~ is.null(.x) || isFALSE(.x))))
})
test_that("as_range_spec() pa... | /tests/testthat/test-range_spec.R | permissive | selesnow/googlesheets4 | R | false | false | 4,410 | r | # as_range_spec() ----
test_that("as_range_spec() rejects hopeless input", {
expect_error(as_range_spec(3), "Can't make a range")
})
test_that("as_range_spec() can deal with nothingness", {
spec <- as_range_spec(NULL)
expect_true(all(map_lgl(spec, ~ is.null(.x) || isFALSE(.x))))
})
test_that("as_range_spec() pa... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/findStations.R
\name{cf_find_station}
\alias{cf_find_station}
\title{Search for Clifro Stations}
\usage{
cf_find_station(..., search = c("name", "region", "network", "latlong"),
datatype, combine = c("all", "any"), status = c("open", "close... | /man/cf_find_station.Rd | no_license | DrRoad/clifro | R | false | true | 4,771 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/findStations.R
\name{cf_find_station}
\alias{cf_find_station}
\title{Search for Clifro Stations}
\usage{
cf_find_station(..., search = c("name", "region", "network", "latlong"),
datatype, combine = c("all", "any"), status = c("open", "close... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/estimate_curve.R
\name{smooth_curves_covariance}
\alias{smooth_curves_covariance}
\title{Perform a non-parametric smoothing of a set of curves for covariance estimation.}
\usage{
smooth_curves_covariance(
curves,
grid = seq(0, 1, length.o... | /man/smooth_curves_covariance.Rd | permissive | StevenGolovkine/funestim | R | false | true | 2,036 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/estimate_curve.R
\name{smooth_curves_covariance}
\alias{smooth_curves_covariance}
\title{Perform a non-parametric smoothing of a set of curves for covariance estimation.}
\usage{
smooth_curves_covariance(
curves,
grid = seq(0, 1, length.o... |
setwd("C:/Users/Roberto/Desktop/rstudio_default/covid/covid_vaccinazioni_ita/wd-vaccinazioni")
library(tidyverse)
library(data.table)
library(lubridate)
options(scipen = 9999999)
vac_all <- fread("https://raw.githubusercontent.com/italia/covid19-opendata-vaccini/master/dati/somministrazioni-vaccini-summary-latest.cs... | /code-vaccinazioni/old/vaccinazioni.R | no_license | volperob/covid_vaccinazioni_ita | R | false | false | 6,887 | r | setwd("C:/Users/Roberto/Desktop/rstudio_default/covid/covid_vaccinazioni_ita/wd-vaccinazioni")
library(tidyverse)
library(data.table)
library(lubridate)
options(scipen = 9999999)
vac_all <- fread("https://raw.githubusercontent.com/italia/covid19-opendata-vaccini/master/dati/somministrazioni-vaccini-summary-latest.cs... |
testlist <- list(A = structure(c(1.24944110113233e-310, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(5L, 7L)), left = 0L, right = 0L, x = numeric(0))
result <- do.call(mgss:::MVP_normalfactor_rcpp,testlist)
str(result) | /mgss/inst/testfiles/MVP_normalfactor_rcpp/AFL_MVP_normalfactor_rcpp/MVP_normalfactor_rcpp_valgrind_files/1615951426-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 292 | r | testlist <- list(A = structure(c(1.24944110113233e-310, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(5L, 7L)), left = 0L, right = 0L, x = numeric(0))
result <- do.call(mgss:::MVP_normalfactor_rcpp,testlist)
str(result) |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Utility_VennDiagram.R
\name{Utility_VennDiagram}
\alias{Utility_VennDiagram}
\alias{vennDiagram}
\title{Venn diagram.}
\usage{
vennDiagram(x, colors = (ggsci::pal_d3())(length(x)),
show_category_names = T)
}
\arguments{
\item{x}{... | /man/Utility_VennDiagram.Rd | permissive | SilenWang/Repitope | R | false | true | 681 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Utility_VennDiagram.R
\name{Utility_VennDiagram}
\alias{Utility_VennDiagram}
\alias{vennDiagram}
\title{Venn diagram.}
\usage{
vennDiagram(x, colors = (ggsci::pal_d3())(length(x)),
show_category_names = T)
}
\arguments{
\item{x}{... |
library(shiny)
library(leaflet)
library(htmltools)
library(DT)
library(jsonlite)
library(dplyr)
library(RColorBrewer)
library(scales)
library(lattice)
library(ggplot2)
library(rsconnect)
library(rlang)
library(ggrepel)
vis_data <- read.csv("pre.csv")
analyticsData<-read.csv("csv_for_inquire.csv")
va <- names(analytic... | /R modelling and shinny app/app.R | no_license | xiao11lam/Covid-19_forecasting_on_ASEAN_countries | R | false | false | 2,667 | r | library(shiny)
library(leaflet)
library(htmltools)
library(DT)
library(jsonlite)
library(dplyr)
library(RColorBrewer)
library(scales)
library(lattice)
library(ggplot2)
library(rsconnect)
library(rlang)
library(ggrepel)
vis_data <- read.csv("pre.csv")
analyticsData<-read.csv("csv_for_inquire.csv")
va <- names(analytic... |
#' Produce an .html report
#'
#' Produce an .html report with information for outbreak/suspicion management
#' @param ppn Ppn numbers (vector of int numbers, comma separeted)
#' @param ppn_obj Path to the list of objects output from svdc package
#' @param firstname Firstname of the person running the report
#' @param l... | /R/report.R | no_license | SVA-SE/svamp | R | false | false | 4,782 | r | #' Produce an .html report
#'
#' Produce an .html report with information for outbreak/suspicion management
#' @param ppn Ppn numbers (vector of int numbers, comma separeted)
#' @param ppn_obj Path to the list of objects output from svdc package
#' @param firstname Firstname of the person running the report
#' @param l... |
# This file is generated by make.paws. Please do not edit here.
#' @importFrom paws.common new_handlers new_service set_config merge_config
NULL
#' IAM Roles Anywhere
#'
#' @description
#' Identity and Access Management Roles Anywhere provides a secure way for
#' your workloads such as servers, containers, and applica... | /cran/paws.security.identity/R/iamrolesanywhere_service.R | permissive | paws-r/paws | R | false | false | 9,253 | r | # This file is generated by make.paws. Please do not edit here.
#' @importFrom paws.common new_handlers new_service set_config merge_config
NULL
#' IAM Roles Anywhere
#'
#' @description
#' Identity and Access Management Roles Anywhere provides a secure way for
#' your workloads such as servers, containers, and applica... |
#!RScript
# args[1] is the data procesed
# args[2] is the total number of configurations for the data processed
library(ggplot2)
library(plyr)
library(reshape2)
library(tools)
args=(commandArgs(TRUE))
processData <- function(data){
#CALCULATE METRICS
data$fpr=data$FP/as.numeric(args[2])
data$fnr=data$FN/as.numer... | /2.metric_view/helpers/2.calculateMetrics.R | no_license | learningconstraints/ICSE-17 | R | false | false | 949 | r | #!RScript
# args[1] is the data procesed
# args[2] is the total number of configurations for the data processed
library(ggplot2)
library(plyr)
library(reshape2)
library(tools)
args=(commandArgs(TRUE))
processData <- function(data){
#CALCULATE METRICS
data$fpr=data$FP/as.numeric(args[2])
data$fnr=data$FN/as.numer... |
#' Random number generation for truncated multivariate Student's t distribution subject to linear inequality constraints
#'
#' \code{rtmvt} simulates truncated multivariate (p-dimensional) Student's t distribution subject to linear inequality constraints. The constraints should be written as a matrix (\code{D}) with ... | /R/rtmvt.R | no_license | cran/tmvmixnorm | R | false | false | 3,917 | r | #' Random number generation for truncated multivariate Student's t distribution subject to linear inequality constraints
#'
#' \code{rtmvt} simulates truncated multivariate (p-dimensional) Student's t distribution subject to linear inequality constraints. The constraints should be written as a matrix (\code{D}) with ... |
demo.dizzysgene<-function(){
simul(N=1e7,nbVilles=3,type="stoc")->a
plot(a,col=c(1,2,5))
pause()
plot(a,z="S",col=c(1,2,5))
pause()
plot(a,z="S",col=c(1,2,5),proj=list(c("time","P")),box=T)
pause()
plot(a,z="S",col="red")
pause()
simul(N=1e7)->a
plot(a)
pause()
b<-simul(a,continue=T,append=T,t0=1000)
plo... | /CODE_dizzys/refreshDIZZYS_2015_10_23/dizzyslan3/dizzys/demo/dizzysgene.r | no_license | ttcgiang/THESE_GitHub | R | false | false | 1,014 | r | demo.dizzysgene<-function(){
simul(N=1e7,nbVilles=3,type="stoc")->a
plot(a,col=c(1,2,5))
pause()
plot(a,z="S",col=c(1,2,5))
pause()
plot(a,z="S",col=c(1,2,5),proj=list(c("time","P")),box=T)
pause()
plot(a,z="S",col="red")
pause()
simul(N=1e7)->a
plot(a)
pause()
b<-simul(a,continue=T,append=T,t0=1000)
plo... |
context("Expectation Maximization Like Least Squares Classifier")
# Simple dataset used in the tests
data(testdata)
modelform <- testdata$modelform
classname<-all.vars(modelform)[1]
D <- testdata$D
D_test <- testdata$D_test
X <- testdata$X
X_u <- testdata$X_u
y <- testdata$y
X_test <- testdata$X_test
y_test <- testda... | /tests/testthat/test-EMLeastSquaresClassifier.R | no_license | biocq/RSSL | R | false | false | 3,162 | r | context("Expectation Maximization Like Least Squares Classifier")
# Simple dataset used in the tests
data(testdata)
modelform <- testdata$modelform
classname<-all.vars(modelform)[1]
D <- testdata$D
D_test <- testdata$D_test
X <- testdata$X
X_u <- testdata$X_u
y <- testdata$y
X_test <- testdata$X_test
y_test <- testda... |
### Read in Phase 1 - staircase procedure #######
# Reads in behavioural data from relevant phase 1 (staircase procedure) .csv files,
# adds few additional columns useful for further analysis, and saves the files
#############################################################################
# LOST FILES
# c(... | /r_phase1.R | no_license | UlfLab/Evidence_Confidence | R | false | false | 3,453 | r | ### Read in Phase 1 - staircase procedure #######
# Reads in behavioural data from relevant phase 1 (staircase procedure) .csv files,
# adds few additional columns useful for further analysis, and saves the files
#############################################################################
# LOST FILES
# c(... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ec2_operations.R
\name{ec2_describe_transit_gateways}
\alias{ec2_describe_transit_gateways}
\title{Describes one or more transit gateways}
\usage{
ec2_describe_transit_gateways(TransitGatewayIds, Filters, MaxResults,
NextToken, DryRun)
}
\a... | /paws/man/ec2_describe_transit_gateways.Rd | permissive | johnnytommy/paws | R | false | true | 2,969 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ec2_operations.R
\name{ec2_describe_transit_gateways}
\alias{ec2_describe_transit_gateways}
\title{Describes one or more transit gateways}
\usage{
ec2_describe_transit_gateways(TransitGatewayIds, Filters, MaxResults,
NextToken, DryRun)
}
\a... |
#Read the data from the file provided from the http://archive.ics.uci.edu/ml/ (UC Irvine Machine Learning Repository).
#The unzipped file should be in the working directory.
data<-read.table("household_power_consumption.txt",sep=";", header= TRUE,stringsAsFactors=FALSE, na.strings = "?")
#Read the data from the first ... | /plot4.R | no_license | lena-stevanoska/ExData_Plotting1 | R | false | false | 1,774 | r | #Read the data from the file provided from the http://archive.ics.uci.edu/ml/ (UC Irvine Machine Learning Repository).
#The unzipped file should be in the working directory.
data<-read.table("household_power_consumption.txt",sep=";", header= TRUE,stringsAsFactors=FALSE, na.strings = "?")
#Read the data from the first ... |
##Prétraitements des données
library(CASdatasets)
library(keras)
library(tidyverse)
library(recipes)
library(glue)
library(zeallot)
library(tfruns)
data("freMTPLfreq")
## Pré-traitement
# on traite Power comme entier;
# Gas, Brand, Region comme facteur;
# toutes les expositions plus élevées qu'1 sont ram... | /Pre-traitement.R | no_license | nibel113/Projet-reseau-de-neurones | R | false | false | 4,729 | r | ##Prétraitements des données
library(CASdatasets)
library(keras)
library(tidyverse)
library(recipes)
library(glue)
library(zeallot)
library(tfruns)
data("freMTPLfreq")
## Pré-traitement
# on traite Power comme entier;
# Gas, Brand, Region comme facteur;
# toutes les expositions plus élevées qu'1 sont ram... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/read_fs_label.R
\name{read.fs.label.native}
\alias{read.fs.label.native}
\title{Read file in FreeSurfer label format}
\usage{
read.fs.label.native(
filepath,
return_one_based_indices = TRUE,
full = FALSE,
metadata = list()
)
}
\argume... | /man/read.fs.label.native.Rd | permissive | dfsp-spirit/freesurferformats | R | false | true | 2,686 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/read_fs_label.R
\name{read.fs.label.native}
\alias{read.fs.label.native}
\title{Read file in FreeSurfer label format}
\usage{
read.fs.label.native(
filepath,
return_one_based_indices = TRUE,
full = FALSE,
metadata = list()
)
}
\argume... |
library(tidybayes)
### Name: data_list
### Title: Data lists for input into Bayesian models
### Aliases: data_list as_data_list as_data_list.default
### as_data_list.numeric as_data_list.logical as_data_list.factor
### as_data_list.character as_data_list.list as_data_list.data.frame
### as_data_list.data_list
#... | /data/genthat_extracted_code/tidybayes/examples/data_list.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 542 | r | library(tidybayes)
### Name: data_list
### Title: Data lists for input into Bayesian models
### Aliases: data_list as_data_list as_data_list.default
### as_data_list.numeric as_data_list.logical as_data_list.factor
### as_data_list.character as_data_list.list as_data_list.data.frame
### as_data_list.data_list
#... |
\name{CAAPhysicalSun_TimeOfStartOfRotation}
\alias{CAAPhysicalSun_TimeOfStartOfRotation}
\title{
CAAPhysicalSun_TimeOfStartOfRotation
}
\description{
CAAPhysicalSun_TimeOfStartOfRotation
}
\usage{
CAAPhysicalSun_TimeOfStartOfRotation(C)
}
\arguments{
\item{C}{
Integer, indicate the Cycles
}
}
\details... | /man/CAAPhysicalSun_TimeOfStartOfRotation.Rd | no_license | helixcn/skycalc | R | false | false | 614 | rd | \name{CAAPhysicalSun_TimeOfStartOfRotation}
\alias{CAAPhysicalSun_TimeOfStartOfRotation}
\title{
CAAPhysicalSun_TimeOfStartOfRotation
}
\description{
CAAPhysicalSun_TimeOfStartOfRotation
}
\usage{
CAAPhysicalSun_TimeOfStartOfRotation(C)
}
\arguments{
\item{C}{
Integer, indicate the Cycles
}
}
\details... |
#' Do arbitrary operations on a tbl.
#'
#' This is a general purpose complement to the specialised manipulation
#' functions [filter()], [select()], [mutate()],
#' [summarise()] and [arrange()]. You can use `do()`
#' to perform arbitrary computation, returning either a data frame or
#' arbitrary objects which will be s... | /R/do.r | permissive | MhAmine/dplyr | R | false | false | 5,400 | r | #' Do arbitrary operations on a tbl.
#'
#' This is a general purpose complement to the specialised manipulation
#' functions [filter()], [select()], [mutate()],
#' [summarise()] and [arrange()]. You can use `do()`
#' to perform arbitrary computation, returning either a data frame or
#' arbitrary objects which will be s... |
# page no. 578
G = ((20*60)*(4*144)/(pi*0.87^2));
mu = 0.33;
D = 0.87/12;
Re = (D*G)/mu;
print(Re);
h1 = 630;
F = 1.25;
h = h1*F;
print(h);
| /Thermodynamics_And_Heat_Power_by_I_Granet_And_M_Bluestein/CH11/EX11.17/Ex11_17.R | permissive | FOSSEE/R_TBC_Uploads | R | false | false | 141 | r | # page no. 578
G = ((20*60)*(4*144)/(pi*0.87^2));
mu = 0.33;
D = 0.87/12;
Re = (D*G)/mu;
print(Re);
h1 = 630;
F = 1.25;
h = h1*F;
print(h);
|
## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
makeCacheMatrix <- function(x = matrix()) {
inv <- NULL
set <- function(y) {
x <<- y
inv <<- NULL
}
get <- function() x
setinv <- function(inverse) inv <<-... | /cachematrix.R | no_license | joharidepur/R-program | R | false | false | 750 | r | ## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
makeCacheMatrix <- function(x = matrix()) {
inv <- NULL
set <- function(y) {
x <<- y
inv <<- NULL
}
get <- function() x
setinv <- function(inverse) inv <<-... |
# The code below can be used to reproduce the results of
# An information-theoretic approach for selecting arms in clinical trials
# by P. Mozgunov and T. Jaki (2019)
# Section 5 with co-primary efficacy endpoints
# The "wdesign-co-primary-code.R" is required to be run prior to the code below.
# WE-II Select-the-Bes... | /Phase-2-Co-Primary-Run.R | no_license | adaptive-designs/inf-theory | R | false | false | 3,032 | r | # The code below can be used to reproduce the results of
# An information-theoretic approach for selecting arms in clinical trials
# by P. Mozgunov and T. Jaki (2019)
# Section 5 with co-primary efficacy endpoints
# The "wdesign-co-primary-code.R" is required to be run prior to the code below.
# WE-II Select-the-Bes... |
#' Add edges and attributes to graph from a table
#' @description Add edges and their attributes to an
#' existing graph object from data in a CSV file or a
#' data frame.
#' @param graph a graph object of class
#' \code{dgr_graph} that is created using
#' \code{create_graph}.
#' @param table either a path to a CSV fil... | /R/add_edges_from_table.R | no_license | dy-kim/DiagrammeR | R | false | false | 11,173 | r | #' Add edges and attributes to graph from a table
#' @description Add edges and their attributes to an
#' existing graph object from data in a CSV file or a
#' data frame.
#' @param graph a graph object of class
#' \code{dgr_graph} that is created using
#' \code{create_graph}.
#' @param table either a path to a CSV fil... |
#'Generate survival times for two endpoints using the joint frailty-copula model for surrogacy
#'
#'Date are generated from the one-step joint frailty-copula model, under the Claton
#'copula function (see \code{\link{jointSurroCopPenal}} for more details)
#'
#'We just considered in this generation, the Gaussian r... | /R/jointSurrCopSimul.R | no_license | cran/frailtypack | R | false | false | 18,515 | r | #'Generate survival times for two endpoints using the joint frailty-copula model for surrogacy
#'
#'Date are generated from the one-step joint frailty-copula model, under the Claton
#'copula function (see \code{\link{jointSurroCopPenal}} for more details)
#'
#'We just considered in this generation, the Gaussian r... |
.onAttach <- function(...) {
packageStartupMessage('Super Learner')
packageStartupMessage('Version: ', utils::packageDescription('SuperLearner')$Version)
packageStartupMessage('Package created on ', utils::packageDescription('SuperLearner')$Date, '\n')
packageStartupMessage('Use SuperLearnerNews() to see change... | /R/zzz.R | no_license | ledell/SuperLearner | R | false | false | 539 | r | .onAttach <- function(...) {
packageStartupMessage('Super Learner')
packageStartupMessage('Version: ', utils::packageDescription('SuperLearner')$Version)
packageStartupMessage('Package created on ', utils::packageDescription('SuperLearner')$Date, '\n')
packageStartupMessage('Use SuperLearnerNews() to see change... |
##' update tree
##'
##'
##' @rdname update-TREE
##' @title \%<\%
##' @param pg ggplot2 object
##' @param x update by x
##' @return updated ggplot object
##' @export
##' @author Yu Guangchuang
##' @examples
##' library("ggplot2")
##' nwk <- system.file("extdata", "sample.nwk", package="treeio")
##' tree <- read.tree(nwk... | /R/operator.R | no_license | lzh93/ggtree | R | false | false | 3,952 | r | ##' update tree
##'
##'
##' @rdname update-TREE
##' @title \%<\%
##' @param pg ggplot2 object
##' @param x update by x
##' @return updated ggplot object
##' @export
##' @author Yu Guangchuang
##' @examples
##' library("ggplot2")
##' nwk <- system.file("extdata", "sample.nwk", package="treeio")
##' tree <- read.tree(nwk... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_qq.R
\name{plot_qq}
\alias{plot_qq}
\title{Plot qqplot}
\usage{
plot_qq(
data = data,
comp.names = NULL,
p.value.flag = "P.Value",
ci = 0.95,
plot.save.to = NULL
)
}
\arguments{
\item{data}{Summary statistics tab... | /man/plot_qq.Rd | no_license | cran/RVA | R | false | true | 1,610 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_qq.R
\name{plot_qq}
\alias{plot_qq}
\title{Plot qqplot}
\usage{
plot_qq(
data = data,
comp.names = NULL,
p.value.flag = "P.Value",
ci = 0.95,
plot.save.to = NULL
)
}
\arguments{
\item{data}{Summary statistics tab... |
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