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 |
|---|---|---|---|---|---|---|---|---|---|
#' Calculate mitigation costs
#'
#' Calculate mitigation costs
#'
#'
#' @param data quitte object
#' @param scenBau baseline scenario name
#' @param scenPol policy scenario name
#' @param yearFrom the startyear
#' @param yearTo the endyear
#' @param nameVar Name of the variable containing consumption. Defaults to
#' "C... | /R/calcMitigationCost.R | no_license | 0UmfHxcvx5J7JoaOhFSs5mncnisTJJ6q/quitte | R | false | false | 2,346 | r | #' Calculate mitigation costs
#'
#' Calculate mitigation costs
#'
#'
#' @param data quitte object
#' @param scenBau baseline scenario name
#' @param scenPol policy scenario name
#' @param yearFrom the startyear
#' @param yearTo the endyear
#' @param nameVar Name of the variable containing consumption. Defaults to
#' "C... |
rm(list=ls())
set.seed(75)
xVec<-sample(0:9,size=10,replace=T)
tmpFn1 <- function(x)
{
x^(1:length(x))
}
tmpFn2 <- function(x)
{
n <- length(x)
(x^(1:n))/(1:n)
}
tmpFn <- function(x)
{
n<-length(x)-2
(x[1:n] + x[2:(n+1)] + x[3:(n+2)])/3
}
tmpFn(c(1:5,6:1))
tmpFn <- function(x)
{
ifelse(x < 0, ... | /Ex3Functions.R | no_license | KrishnaGMohan/RExercises | R | false | false | 3,509 | r | rm(list=ls())
set.seed(75)
xVec<-sample(0:9,size=10,replace=T)
tmpFn1 <- function(x)
{
x^(1:length(x))
}
tmpFn2 <- function(x)
{
n <- length(x)
(x^(1:n))/(1:n)
}
tmpFn <- function(x)
{
n<-length(x)-2
(x[1:n] + x[2:(n+1)] + x[3:(n+2)])/3
}
tmpFn(c(1:5,6:1))
tmpFn <- function(x)
{
ifelse(x < 0, ... |
# test_igraph_inv.R
# Created by Disa Mhembere on 2013-12-31.
# Email: disa@jhu.edu
# Copyright (c) 2013. All rights reserved.
require(igraph)
require(argparse)
parser <- ArgumentParser(description="Run same invariants as MROCP on igraphs")
parser$add_argument("gfn", help="The graph file name")
parser$add_argument("... | /MR-OCP/MROCPdjango/computation/tests/test_igraph_inv.R | permissive | gkiar/ndgrutedb | R | false | false | 1,387 | r | # test_igraph_inv.R
# Created by Disa Mhembere on 2013-12-31.
# Email: disa@jhu.edu
# Copyright (c) 2013. All rights reserved.
require(igraph)
require(argparse)
parser <- ArgumentParser(description="Run same invariants as MROCP on igraphs")
parser$add_argument("gfn", help="The graph file name")
parser$add_argument("... |
#' Submit an expression to be evaluated to multiple jobs.
#' @param expr An expression to be passed to Slurm.
#' @template slurm
#' @template job_name-tmp_path
#' @template sbatch_opt
#' @template rscript_opt
#' @template njobs
#' @return A list of length `njobs`.
#' @export
Slurm_EvalQ <- function(
expr,
njobs ... | /R/Slurm_EvalQ.R | permissive | josezea/slurmR | R | false | false | 2,899 | r | #' Submit an expression to be evaluated to multiple jobs.
#' @param expr An expression to be passed to Slurm.
#' @template slurm
#' @template job_name-tmp_path
#' @template sbatch_opt
#' @template rscript_opt
#' @template njobs
#' @return A list of length `njobs`.
#' @export
Slurm_EvalQ <- function(
expr,
njobs ... |
##' Additional Themes and Theme Components for 'ggplot2' based on OCHA graphic styles
##'
##' A compilation of extra themes and theme components for 'ggplot2'
##' The core theme: `theme_ocha`
##'
##'
##' @name ochathemes-package
##' @aliases ochathemes
##' @docType package
##' @author \email{mail@ahmadoudicko.com}
##'... | /R/ochathemes-package.R | permissive | mmusori/ochathemes | R | false | false | 344 | r | ##' Additional Themes and Theme Components for 'ggplot2' based on OCHA graphic styles
##'
##' A compilation of extra themes and theme components for 'ggplot2'
##' The core theme: `theme_ocha`
##'
##'
##' @name ochathemes-package
##' @aliases ochathemes
##' @docType package
##' @author \email{mail@ahmadoudicko.com}
##'... |
miRDB <- function(searchBox = NA, searchType = c("miRNA", "gene"), Species = c("Human", "Mouse")){
suppressWarnings(suppressPackageStartupMessages({
library(httr)
library(curl)
library(rlist)
library(tidyverse)
library(rvest)} ))
headers <- c('Accept'='text/html,application/xhtml+xml,applicati... | /R/miRDB.R | no_license | shitiezhu/BioMedR | R | false | false | 1,530 | r | miRDB <- function(searchBox = NA, searchType = c("miRNA", "gene"), Species = c("Human", "Mouse")){
suppressWarnings(suppressPackageStartupMessages({
library(httr)
library(curl)
library(rlist)
library(tidyverse)
library(rvest)} ))
headers <- c('Accept'='text/html,application/xhtml+xml,applicati... |
#install.packages('RSQLite')
library(RSQLite)
#lier ce script et nettoyage_equipes_1-7.r
bd_cours <- read.csv2('bd_cours_1-7.csv', header = T)
bd_liens <- read.csv2('bd_liens_1-7.csv', header = T)
bd_etudiants <- read.csv2('bd_etudiants_1-7.csv', header = T)
tables.db <- dbConnect(SQLite(), dbname="tables.db")
#cre... | /injection_données.R | no_license | elysepaquette/lesreseaux | R | false | false | 2,642 | r | #install.packages('RSQLite')
library(RSQLite)
#lier ce script et nettoyage_equipes_1-7.r
bd_cours <- read.csv2('bd_cours_1-7.csv', header = T)
bd_liens <- read.csv2('bd_liens_1-7.csv', header = T)
bd_etudiants <- read.csv2('bd_etudiants_1-7.csv', header = T)
tables.db <- dbConnect(SQLite(), dbname="tables.db")
#cre... |
# Plot Functionality for package bpwpm
#-------------------------------------------------------------------------------
#' Generic bpwpm plotting
#'
#' Once a bpwpm has been run using the function \code{\link{bpwpm_gibbs}}, the
#' chains can be plotted and hence evaluated. This generic function builds sets
#' of plots... | /R/plot_funcs.R | no_license | PaoloLuciano/bpwpm | R | false | false | 13,027 | r | # Plot Functionality for package bpwpm
#-------------------------------------------------------------------------------
#' Generic bpwpm plotting
#'
#' Once a bpwpm has been run using the function \code{\link{bpwpm_gibbs}}, the
#' chains can be plotted and hence evaluated. This generic function builds sets
#' of plots... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/grcm38_tx2gene.R
\docType{data}
\name{grcm38_tx2gene}
\alias{grcm38_tx2gene}
\title{Mouse transcripts to genes}
\format{An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 129826 rows and 2 columns.}
\source{
\... | /man/grcm38_tx2gene.Rd | no_license | aaronwolen/annotables | R | false | true | 652 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/grcm38_tx2gene.R
\docType{data}
\name{grcm38_tx2gene}
\alias{grcm38_tx2gene}
\title{Mouse transcripts to genes}
\format{An object of class \code{tbl_df} (inherits from \code{tbl}, \code{data.frame}) with 129826 rows and 2 columns.}
\source{
\... |
#' Produce a calibration plot for a set of predicted probabilities for a binary classifier.
#' @export
#' @import ggplot2
#' @import data.table
#' @importFrom patchwork plot_layout
#' @importFrom Hmisc binconf
#'
#' @param form A formula where the left-hand side is the variable representing the observed outcome, 0 or 1... | /R/calib_plot.R | no_license | gweissman/gmish | R | false | false | 3,508 | r | #' Produce a calibration plot for a set of predicted probabilities for a binary classifier.
#' @export
#' @import ggplot2
#' @import data.table
#' @importFrom patchwork plot_layout
#' @importFrom Hmisc binconf
#'
#' @param form A formula where the left-hand side is the variable representing the observed outcome, 0 or 1... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fitted.FPCAder.R
\name{fitted.FPCAder}
\alias{fitted.FPCAder}
\title{Fitted functional sample from FPCAder object}
\usage{
\method{fitted}{FPCAder}(object, K = NULL, ...)
}
\arguments{
\item{object}{A object of class FPCA returned by the func... | /man/fitted.FPCAder.Rd | no_license | rogersguo/tPACE | R | false | true | 1,252 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fitted.FPCAder.R
\name{fitted.FPCAder}
\alias{fitted.FPCAder}
\title{Fitted functional sample from FPCAder object}
\usage{
\method{fitted}{FPCAder}(object, K = NULL, ...)
}
\arguments{
\item{object}{A object of class FPCA returned by the func... |
## Read in the data
# Data are at http://www.stat.columbia.edu/~gelman/arm/examples/arsenic
library("arm")
wells <- read.table ("~/Dropbox/Work/Harvard/Wolkovich Lab/Gelman_Hill/ARM_Data/arsenic/wells.dat")
attach.all (wells)
## Histogram on distance (Figure 5.8)
hist (dist, breaks=seq(0,10+max(dist[!is.na(... | /gelmanhill_stuff/Book_Codes/Ch.5/5.4_Logistic regression_wells in Bangladesh.R | no_license | lizzieinvancouver/gelmanhill | R | false | false | 3,600 | r | ## Read in the data
# Data are at http://www.stat.columbia.edu/~gelman/arm/examples/arsenic
library("arm")
wells <- read.table ("~/Dropbox/Work/Harvard/Wolkovich Lab/Gelman_Hill/ARM_Data/arsenic/wells.dat")
attach.all (wells)
## Histogram on distance (Figure 5.8)
hist (dist, breaks=seq(0,10+max(dist[!is.na(... |
## Test file for the IRSDataLoader object
library(QFFixedIncome)
testIRSDataLoader <- function()
{
# test bad inputss
loaderSample <- IRSDataLoader()
irsSample <- GenericIRS()
irsSample$setDefault(tenor = "5y")
shouldBomb(loaderSample$getSpreads())
shouldBomb(loaderSample$... | /R/src/QFFixedIncome/tests/testIRSDataLoader.R | no_license | rsheftel/ratel | R | false | false | 5,049 | r | ## Test file for the IRSDataLoader object
library(QFFixedIncome)
testIRSDataLoader <- function()
{
# test bad inputss
loaderSample <- IRSDataLoader()
irsSample <- GenericIRS()
irsSample$setDefault(tenor = "5y")
shouldBomb(loaderSample$getSpreads())
shouldBomb(loaderSample$... |
#' getVariantsColors
#'
#' @description
#'
#' Given the reference and alternative for a set of variants, assigns a color
#' to each of them
#'
#' @details
#'
#' The function creates an nucleotide substitution identifier with for each
#' variant and uses it to query the color.table lookup table. If color.table
... | /R/getVariantsColors.R | no_license | jing-wan/karyoploteR | R | false | false | 3,151 | r | #' getVariantsColors
#'
#' @description
#'
#' Given the reference and alternative for a set of variants, assigns a color
#' to each of them
#'
#' @details
#'
#' The function creates an nucleotide substitution identifier with for each
#' variant and uses it to query the color.table lookup table. If color.table
... |
\name{max.subtree.rfsrc}
\alias{max.subtree.rfsrc}
\alias{max.subtree}
\title{Acquire Maximal Subtree Information}
\description{
Extract maximal subtree information from a RF-SRC object. Used for
variable selection and identifying interactions between variables.
}
\usage{\method{max.subtree}{rfsrc}(object,
m... | /man/max.subtree.rfsrc.Rd | no_license | nkuwangkai/randomForestSRC | R | false | false | 6,560 | rd | \name{max.subtree.rfsrc}
\alias{max.subtree.rfsrc}
\alias{max.subtree}
\title{Acquire Maximal Subtree Information}
\description{
Extract maximal subtree information from a RF-SRC object. Used for
variable selection and identifying interactions between variables.
}
\usage{\method{max.subtree}{rfsrc}(object,
m... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/link_time_performance_integrated.R
\name{link_time_performance_integrated}
\alias{link_time_performance_integrated}
\title{Integration of link time performance}
\usage{
link_time_performance_integrated(flow, t0, capacity, alpha = 0.15, beta =... | /man/link_time_performance_integrated.Rd | no_license | douglascm/trafficr | R | false | true | 769 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/link_time_performance_integrated.R
\name{link_time_performance_integrated}
\alias{link_time_performance_integrated}
\title{Integration of link time performance}
\usage{
link_time_performance_integrated(flow, t0, capacity, alpha = 0.15, beta =... |
#
# This is the server logic of a Shiny web application. You can run the
# application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
function(input, output, session) {
# input$date and others are Date... | /server.R | no_license | HossamMHassan/App | R | false | false | 803 | r | #
# This is the server logic of a Shiny web application. You can run the
# application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
function(input, output, session) {
# input$date and others are Date... |
test_that("rws_connect", {
expect_error(
rws_connect(":memory:", exists = TRUE),
"File ':memory:' must already exist."
)
conn <- rws_connect(":memory:")
expect_true(vld_sqlite_conn(conn, connected = TRUE))
rws_disconnect(conn)
expect_true(vld_sqlite_conn(conn, connected = FALSE))
})
| /tests/testthat/test-connection.R | permissive | poissonconsulting/readwritesqlite | R | false | false | 304 | r | test_that("rws_connect", {
expect_error(
rws_connect(":memory:", exists = TRUE),
"File ':memory:' must already exist."
)
conn <- rws_connect(":memory:")
expect_true(vld_sqlite_conn(conn, connected = TRUE))
rws_disconnect(conn)
expect_true(vld_sqlite_conn(conn, connected = FALSE))
})
|
#Plot 3
require(lubridate)
require(ggplot2)
#Download and read files
if(!(file.exists("Source_Classification_Code.rds"))){
download.file("http://d396qusza40orc.cloudfront.net/exdata%2Fdata%2FNEI_data.zip", "dataset.zip")
unzip("dataset.zip")
file.remove("dataset.zip")
}
#Variable creation and general cleanup
S... | /plot3.R | no_license | joaoclemencio/EDA-Course-Project-2 | R | false | false | 1,501 | r | #Plot 3
require(lubridate)
require(ggplot2)
#Download and read files
if(!(file.exists("Source_Classification_Code.rds"))){
download.file("http://d396qusza40orc.cloudfront.net/exdata%2Fdata%2FNEI_data.zip", "dataset.zip")
unzip("dataset.zip")
file.remove("dataset.zip")
}
#Variable creation and general cleanup
S... |
## ---------- dataprep.R ----------- ##
# #
# fastaconc #
# df2fasta #
# d.phy2df #
# #
## --------------------------------- ##
## ------------------------------------... | /R/dataprep.R | no_license | cran/EnvNJ | R | false | false | 4,428 | r | ## ---------- dataprep.R ----------- ##
# #
# fastaconc #
# df2fasta #
# d.phy2df #
# #
## --------------------------------- ##
## ------------------------------------... |
##Loading and reading the file
dataFile <- "./household_power_consumption.txt"
data <- read.table(dataFile, header=TRUE, sep=";", stringsAsFactors=FALSE, dec=".")
subSetData <- data[data$Date %in% c("1/2/2007","2/2/2007") ,]
##plotting graph 1
#str(subSetData)
globalActivePower <- as.numeric(subSetData$Global_active_po... | /plot1.R | no_license | kellywale/Exploratorydataplotting | R | false | false | 477 | r | ##Loading and reading the file
dataFile <- "./household_power_consumption.txt"
data <- read.table(dataFile, header=TRUE, sep=";", stringsAsFactors=FALSE, dec=".")
subSetData <- data[data$Date %in% c("1/2/2007","2/2/2007") ,]
##plotting graph 1
#str(subSetData)
globalActivePower <- as.numeric(subSetData$Global_active_po... |
### 6.4
# [for the sake of practice, here I use a different approach than in the previous exercise.
# this approach is more general as it is not limited to two states as before]
# random walk parameters:
p <- .3
q <- .3
r <- .4
p1<- .2
q1<- .2
r1<- .6
... | /hw2/hw2_6.4_sb.R | no_license | vhurtadol/POLI574 | R | false | false | 1,820 | r | ### 6.4
# [for the sake of practice, here I use a different approach than in the previous exercise.
# this approach is more general as it is not limited to two states as before]
# random walk parameters:
p <- .3
q <- .3
r <- .4
p1<- .2
q1<- .2
r1<- .6
... |
library(plotrix)
library(readxl)
pob<-read_xlsx("azcapob1.xlsx")
attach(pob)
pob1<-pob[,-1]
pob2<-t(pob1)
colnames(pob2)<- c("40-44", "45 a 49", "50 a 54", "55 a 59")
pob2
barp(pob2, names.arg = colnames(pob2), cex.axis = 0.7,
col=rainbow(2), cylindrical = TRUE, ylim = c(0,19000),
shadow = FALSE, staxx ... | /Rstudioazcapotzalco/poblacion/R/azcagrafo3.R | no_license | davidlechuga/OPCD | R | false | false | 635 | r | library(plotrix)
library(readxl)
pob<-read_xlsx("azcapob1.xlsx")
attach(pob)
pob1<-pob[,-1]
pob2<-t(pob1)
colnames(pob2)<- c("40-44", "45 a 49", "50 a 54", "55 a 59")
pob2
barp(pob2, names.arg = colnames(pob2), cex.axis = 0.7,
col=rainbow(2), cylindrical = TRUE, ylim = c(0,19000),
shadow = FALSE, staxx ... |
# Platform Repository Service
#
# Platform Repository Service - Sage Bionetworks Platform
#
# The version of the OpenAPI document: develop-SNAPSHOT
# Contact: thomas.yu@sagebionetworks.org
# Generated by: https://openapi-generator.tech
#' @docType class
#' @title SubmissionStatusEnum
#'
#' @description SubmissionStat... | /R/submission_status_enum.R | no_license | thomasyu888/synr-sdk-client | R | false | false | 1,905 | r | # Platform Repository Service
#
# Platform Repository Service - Sage Bionetworks Platform
#
# The version of the OpenAPI document: develop-SNAPSHOT
# Contact: thomas.yu@sagebionetworks.org
# Generated by: https://openapi-generator.tech
#' @docType class
#' @title SubmissionStatusEnum
#'
#' @description SubmissionStat... |
## Copyright 2013-2015 Stefan Widgren and Maria Noremark,
## National Veterinary Institute, Sweden
##
## Licensed under the EUPL, Version 1.1 or - as soon they
## will be approved by the European Commission - subsequent
## versions of the EUPL (the "Licence");
## You may not use this work except in compliance with the
... | /EpiContactTrace/R/in-degree.r | no_license | ingted/R-Examples | R | false | false | 7,556 | r | ## Copyright 2013-2015 Stefan Widgren and Maria Noremark,
## National Veterinary Institute, Sweden
##
## Licensed under the EUPL, Version 1.1 or - as soon they
## will be approved by the European Commission - subsequent
## versions of the EUPL (the "Licence");
## You may not use this work except in compliance with the
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/drug_targets_node_parser.R
\name{parse_drug_targets_polypeptides_pfams}
\alias{parse_drug_targets_polypeptides_pfams}
\title{Extracts the drug targets polypeptides pfams
element and return data as data frame.}
\usage{
parse_drug_targets_poly... | /man/parse_drug_targets_polypeptides_pfams.Rd | no_license | Sparklingredstar/dbparser | R | false | true | 2,606 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/drug_targets_node_parser.R
\name{parse_drug_targets_polypeptides_pfams}
\alias{parse_drug_targets_polypeptides_pfams}
\title{Extracts the drug targets polypeptides pfams
element and return data as data frame.}
\usage{
parse_drug_targets_poly... |
`LDuncan` <- function(anova,which="",conf.level=0.95)
UseMethod("LDuncan") | /R/LDuncan.R | no_license | cran/laercio | R | false | false | 75 | r | `LDuncan` <- function(anova,which="",conf.level=0.95)
UseMethod("LDuncan") |
##' Calculate Mohn's Rho values for select quantities
##'
##' Function calculates:
##' (1) a rho value for the ending year for each retrospective relative to the reference model
##' as in Mohn (1999),
##' (2) a "Wood's Hole Mohn's Rho", which is a rho value averaged across all years for each
##' retrospective rel... | /R/SSmohnsrho.R | no_license | cran/r4ss | R | false | false | 6,555 | r | ##' Calculate Mohn's Rho values for select quantities
##'
##' Function calculates:
##' (1) a rho value for the ending year for each retrospective relative to the reference model
##' as in Mohn (1999),
##' (2) a "Wood's Hole Mohn's Rho", which is a rho value averaged across all years for each
##' retrospective rel... |
#' @export
Ops.optmatch.dlist <- function (e1, e2=NULL)
{
ok <- switch(.Generic, "%%" = , "%/%" = FALSE, TRUE)
if (!ok) {
warning(.Generic, " not meaningful for matching distances; returning 1st arg")
return(e1)
}
unary <- nargs() == 1
if (nchar(.Method[1])) {
rn1 <- attr(e1, ... | /R/Ops.optmatch.dlist.R | permissive | markmfredrickson/optmatch | R | false | false | 4,573 | r | #' @export
Ops.optmatch.dlist <- function (e1, e2=NULL)
{
ok <- switch(.Generic, "%%" = , "%/%" = FALSE, TRUE)
if (!ok) {
warning(.Generic, " not meaningful for matching distances; returning 1st arg")
return(e1)
}
unary <- nargs() == 1
if (nchar(.Method[1])) {
rn1 <- attr(e1, ... |
genlogCompleteStartValues <- function(data,
timeVar = 1,
yVar = 2,
phaseVar = NULL,
baselineMeasurements = NULL, ### Was nA
y... | /R/genlogCompleteStartValues.R | no_license | DBoegner/userfriendlyscience | R | false | false | 7,274 | r | genlogCompleteStartValues <- function(data,
timeVar = 1,
yVar = 2,
phaseVar = NULL,
baselineMeasurements = NULL, ### Was nA
y... |
#' combine two gg_partial objects
#'
#' @description
#' The \code{combine.gg_partial} function assumes the two \code{\link{gg_partial}}
#' objects were generated from the same \code{\link[randomForestSRC]{rfsrc}}
#' object. So, the function joins along the \code{\link{gg_partial}} list item
#' names (one per partial... | /R/combine.gg_partial.R | no_license | mingrisch/ggRandomForests | R | false | false | 3,600 | r | #' combine two gg_partial objects
#'
#' @description
#' The \code{combine.gg_partial} function assumes the two \code{\link{gg_partial}}
#' objects were generated from the same \code{\link[randomForestSRC]{rfsrc}}
#' object. So, the function joins along the \code{\link{gg_partial}} list item
#' names (one per partial... |
library(shiny)
library(shinydashboard)
library(purrr)
server <- function(input, output, session) {
###########################################################################
# Settings
###########################################################################
i18n <- reactive({
selected <- input$selected... | /server.R | permissive | pablo-vivas/ProbabilityDistributionsViewer | R | false | false | 5,625 | r | library(shiny)
library(shinydashboard)
library(purrr)
server <- function(input, output, session) {
###########################################################################
# Settings
###########################################################################
i18n <- reactive({
selected <- input$selected... |
library(ggplot2movies)
library(car)
data(movies)
attach(movies)
View(movies) # przegląd wszystkich danych
ls(movies) # lista zmiennnych
# zmniejszamy ilość porównywanych danych, ponieważ dla tak dużej ilości porównywanych danych
# (58788) hipoteza zerowa będzie niemalże na 100% pewna. Dla możliwości wyciągnięcia wn... | /src/R/RAPORT 2 2.R | permissive | NataliaEwa/AppliedMathematics | R | false | false | 6,386 | r | library(ggplot2movies)
library(car)
data(movies)
attach(movies)
View(movies) # przegląd wszystkich danych
ls(movies) # lista zmiennnych
# zmniejszamy ilość porównywanych danych, ponieważ dla tak dużej ilości porównywanych danych
# (58788) hipoteza zerowa będzie niemalże na 100% pewna. Dla możliwości wyciągnięcia wn... |
Sys.setlocale("LC_ALL", "C")
setwd("C:\\R\\Analytics Edge")
getwd()
emails = read.csv("emails.csv", stringsAsFactors=FALSE)
str(emails)
summary(emails$spam==1)
library(tm)
library(SnowballC)
corpus = Corpus(VectorSource(emails$text))
corpus
corpus[[1]]
corpus = tm_map(corpus, tolower)
corpus = tm_map(corpus, PlainT... | /Week 5 - Text Mining/Asignment 5c/Spam from Ham.R | no_license | AlfonsoCampos/The-Analytics-Edge | R | false | false | 3,172 | r | Sys.setlocale("LC_ALL", "C")
setwd("C:\\R\\Analytics Edge")
getwd()
emails = read.csv("emails.csv", stringsAsFactors=FALSE)
str(emails)
summary(emails$spam==1)
library(tm)
library(SnowballC)
corpus = Corpus(VectorSource(emails$text))
corpus
corpus[[1]]
corpus = tm_map(corpus, tolower)
corpus = tm_map(corpus, PlainT... |
#Task 1
# Setting up working directory
setwd("C:/Users/victor/Desktop/Economics_R_Code")
library(tidyverse)
library(sf)
#Task 2
#Downloaded Counties and equavilent data
#Shape file are located in working directory file 'Dataset' of my directory
#Task 3
#Reading the nytiowa data set and tidy it up (reuse code form la... | /Scripts/Tran7.R | no_license | VictorTran808/Economics_R_Code | R | false | false | 1,247 | r | #Task 1
# Setting up working directory
setwd("C:/Users/victor/Desktop/Economics_R_Code")
library(tidyverse)
library(sf)
#Task 2
#Downloaded Counties and equavilent data
#Shape file are located in working directory file 'Dataset' of my directory
#Task 3
#Reading the nytiowa data set and tidy it up (reuse code form la... |
#Goncala version riskvalRuns
source("powerTests.r")
#source("powerTests2.r")
#total sample size 10000
Samp <- 10000 #Casamp = n; Cosamp = Samp-n
rounds = 10000
disfr = 0.0001
sims <- data.frame()
#cat("Ncases Ncontrols AF Risk Power_Log Power_Score Power_Prop Power_Chi Disease_frequency\n")
for (Cosamp in c(9000, 80... | /riskValRuns.R | no_license | lankrist/ph_meta-analysis | R | false | false | 956 | r | #Goncala version riskvalRuns
source("powerTests.r")
#source("powerTests2.r")
#total sample size 10000
Samp <- 10000 #Casamp = n; Cosamp = Samp-n
rounds = 10000
disfr = 0.0001
sims <- data.frame()
#cat("Ncases Ncontrols AF Risk Power_Log Power_Score Power_Prop Power_Chi Disease_frequency\n")
for (Cosamp in c(9000, 80... |
#packages installed= data.table, dplyr, formattable, tidyr using function install.packages("") for example install.packages ("tidyr")
library(tidyr)
library(ggplot2)
library(data.table)
library(dplyr)
library(formattable)
library(qwraps2)
library(stringr)
#Actual.Eco.Site is a column I added to each TerrADat ... | /Unknown Codes remaining in data.R | no_license | bewheeler/AIM_Annual_Report_Code | R | false | false | 4,588 | r | #packages installed= data.table, dplyr, formattable, tidyr using function install.packages("") for example install.packages ("tidyr")
library(tidyr)
library(ggplot2)
library(data.table)
library(dplyr)
library(formattable)
library(qwraps2)
library(stringr)
#Actual.Eco.Site is a column I added to each TerrADat ... |
plot3<- function() {
# read data
project_elec<-read.table("household_power_consumption.txt",
sep=";",header=TRUE)
# convert to numeric
project_elec$Sub_metering_1<-as.numeric(project_elec$Sub_metering_1)
project_elec$Sub_metering_2<-as.numeric(project_elec$Sub_metering_2)
pr... | /plot3.R | no_license | unknowncutename/exploratorydata | R | false | false | 1,436 | r | plot3<- function() {
# read data
project_elec<-read.table("household_power_consumption.txt",
sep=";",header=TRUE)
# convert to numeric
project_elec$Sub_metering_1<-as.numeric(project_elec$Sub_metering_1)
project_elec$Sub_metering_2<-as.numeric(project_elec$Sub_metering_2)
pr... |
#' @title Gather spectra from list of spectral data into a tibble object
#' @description Gather specta and spectrometer metadata from list into a tibble.
#' Spectra and wavenumbers are stored in list-columns. A tibble is an extended
#' data frame and each spectrum can contain complex data and metadata that
#' are in a ... | /Soil-Predictions-Example/Functions/simplerspec/gather-spc.R | no_license | lusensn/Soil-Predictions-MIR | R | false | false | 2,515 | r | #' @title Gather spectra from list of spectral data into a tibble object
#' @description Gather specta and spectrometer metadata from list into a tibble.
#' Spectra and wavenumbers are stored in list-columns. A tibble is an extended
#' data frame and each spectrum can contain complex data and metadata that
#' are in a ... |
LabelPlot<-function(Data,Sel1,Sel2=NULL,col1,col2=NULL,...){
x=Data$Clust
d_temp <- stats::dendrapply(stats::as.dendrogram(x,hang=0.02),LabelCols,Sel1,Sel2,col1,col2)
graphics::plot(d_temp,nodePar=list(pch=NA),edgePar=list(lwd=2),ylab="Height",font.axis=2,font.lab=2,font=2,...)
graphics::axis(side = 2, lw... | /IntClust/R/Labelplot.R | no_license | ingted/R-Examples | R | false | false | 331 | r | LabelPlot<-function(Data,Sel1,Sel2=NULL,col1,col2=NULL,...){
x=Data$Clust
d_temp <- stats::dendrapply(stats::as.dendrogram(x,hang=0.02),LabelCols,Sel1,Sel2,col1,col2)
graphics::plot(d_temp,nodePar=list(pch=NA),edgePar=list(lwd=2),ylab="Height",font.axis=2,font.lab=2,font=2,...)
graphics::axis(side = 2, lw... |
# Teresita M. Porter, Sept. 9, 2019
library(vegan)
library(reshape2)
library(gridExtra)
library(grid)
library(ggplot2)
library(plyr)
library(data.table)
library("car")
library(stringr)
library("ggpubr")
# Read infile
A<-read.table(file="matrix.csv", head=TRUE, sep=",")
# Select phylum Arthropoda only
B<-A[A$Phylum==... | /scripts/Fig1_Richness.R | permissive | Hajibabaei-Lab/HajibabaeiEtAl2019b_benthos_vs_water | R | false | false | 3,085 | r | # Teresita M. Porter, Sept. 9, 2019
library(vegan)
library(reshape2)
library(gridExtra)
library(grid)
library(ggplot2)
library(plyr)
library(data.table)
library("car")
library(stringr)
library("ggpubr")
# Read infile
A<-read.table(file="matrix.csv", head=TRUE, sep=",")
# Select phylum Arthropoda only
B<-A[A$Phylum==... |
plot.scaleCoef <-
function(x,
add=FALSE, # logical, if true add plot to current plot
offsetby=0, # amount on x-axis by which to offset the plotted
# estimates and confidence intervals, useful when add is TRUE
... | /R/plot.scaleCoef.R | no_license | cran/scaleCoef | R | false | false | 10,626 | r | plot.scaleCoef <-
function(x,
add=FALSE, # logical, if true add plot to current plot
offsetby=0, # amount on x-axis by which to offset the plotted
# estimates and confidence intervals, useful when add is TRUE
... |
library(igraph)
configModel <- function (degrees = rep(n, floor(n / 2)),
membership = rep(1, n), P = NULL) {
# Checking P
if (!is.null(P)) {
if (!is.matrix(P))
stop('P must be a matrix\n')
K <- max(membership)
if (nrow(P) != K)
stop('P must have K rows\n')
}
... | /configModel.R | no_license | jpalowitch/configModel | R | false | false | 1,457 | r | library(igraph)
configModel <- function (degrees = rep(n, floor(n / 2)),
membership = rep(1, n), P = NULL) {
# Checking P
if (!is.null(P)) {
if (!is.matrix(P))
stop('P must be a matrix\n')
K <- max(membership)
if (nrow(P) != K)
stop('P must have K rows\n')
}
... |
#' Summarize the Multiple Imputation of Multivariate Regression Discontinuity Estimation
#'
#' \code{summary.mrdi} is a \code{summary} method for class \code{"mrdi"}
#'
#' @method summary mrdi
#'
#' @param object An object of class \code{"mrdi"}, usually a result of a call to
#' \code{\link{mrd_impute}} with \code{... | /R/summary.mrdi.R | no_license | kimberlywebb/rddapp | R | false | false | 12,587 | r | #' Summarize the Multiple Imputation of Multivariate Regression Discontinuity Estimation
#'
#' \code{summary.mrdi} is a \code{summary} method for class \code{"mrdi"}
#'
#' @method summary mrdi
#'
#' @param object An object of class \code{"mrdi"}, usually a result of a call to
#' \code{\link{mrd_impute}} with \code{... |
build.dist.struct <-
function(z, X, exact = NULL, calip.option = 'propensity', calip.cov = NULL, caliper = 0.2, verbose = FALSE){
cal.penalty <- 100
if(is.null(exact)) exact = rep(1, length(z))
if(!(calip.option %in% c('propensity','user','none'))){
stop('Invalid calip.option specified.')
}
if (is.vector(X... | /R/build.dist.struct.R | no_license | cran/rcbalance | R | false | false | 3,983 | r | build.dist.struct <-
function(z, X, exact = NULL, calip.option = 'propensity', calip.cov = NULL, caliper = 0.2, verbose = FALSE){
cal.penalty <- 100
if(is.null(exact)) exact = rep(1, length(z))
if(!(calip.option %in% c('propensity','user','none'))){
stop('Invalid calip.option specified.')
}
if (is.vector(X... |
###### categorical variable and factors
marital.status <- c("Married","Married","Single","Married","Divorced","Widowed","Divorced")
?str() #### display the structure of the object
str(marital.status)
typeof(marital.status)
##### factor and levels
marital.factor <- factor(marital.status)
marital.factor
str(marit... | /CodeBase/5_Categorical_Variable_And_factors.R | no_license | akashishu777/R-Practice | R | false | false | 964 | r |
###### categorical variable and factors
marital.status <- c("Married","Married","Single","Married","Divorced","Widowed","Divorced")
?str() #### display the structure of the object
str(marital.status)
typeof(marital.status)
##### factor and levels
marital.factor <- factor(marital.status)
marital.factor
str(marit... |
prompt_runtime_factory <- function() {
last <- proc.time()
last[] <- NA_real_
function(...) {
diff <- proc.time() - last
elapsed <- sum(diff) - diff["elapsed"]
last <<- proc.time()
if (!is.na(elapsed) && elapsed > 1) {
paste0(round(elapsed), "s > ")
} else {
"> "
}
}
}
#'... | /R/prompts.R | no_license | jimhester/prompt | R | false | false | 1,638 | r |
prompt_runtime_factory <- function() {
last <- proc.time()
last[] <- NA_real_
function(...) {
diff <- proc.time() - last
elapsed <- sum(diff) - diff["elapsed"]
last <<- proc.time()
if (!is.na(elapsed) && elapsed > 1) {
paste0(round(elapsed), "s > ")
} else {
"> "
}
}
}
#'... |
#' Plot Google Earth images obtained through dismo::gmap
#'
#' This function is very slightly modified from \code{.plotCT} function in \code{raster} package to avoid producing an empty plot before the actual Google image.
#'
#' @param x RasterLayer, as obtained through \code{\link[dismo]{gmap}}.
#' @param maxpixels in... | /R/plot_gmap.R | no_license | raianu191/rSDM | R | false | false | 3,634 | r |
#' Plot Google Earth images obtained through dismo::gmap
#'
#' This function is very slightly modified from \code{.plotCT} function in \code{raster} package to avoid producing an empty plot before the actual Google image.
#'
#' @param x RasterLayer, as obtained through \code{\link[dismo]{gmap}}.
#' @param maxpixels in... |
##############################################################################################################################################################################################
#Random Forest for Northern California to investigate the LU variables directly related to the MMI scores....
#16March2015
######... | /misc R scripts/NC_RandomForest/NC_RF_MMItoLU.R | no_license | usubuglab/AIM_2016 | R | false | false | 13,730 | r | ##############################################################################################################################################################################################
#Random Forest for Northern California to investigate the LU variables directly related to the MMI scores....
#16March2015
######... |
# V-fold Cross-validation wrapper for SuperLearner
CV.SuperLearner <- function(Y, X, V = NULL, family = gaussian(), SL.library, method = 'method.NNLS', id = NULL, verbose = FALSE, control = list(saveFitLibrary = FALSE), cvControl = list(), innerCvControl = list(), obsWeights = NULL, saveAll = TRUE, parallel = "seq", e... | /R/CV.SuperLearner.R | no_license | frbl/SuperLearner | R | false | false | 5,986 | r | # V-fold Cross-validation wrapper for SuperLearner
CV.SuperLearner <- function(Y, X, V = NULL, family = gaussian(), SL.library, method = 'method.NNLS', id = NULL, verbose = FALSE, control = list(saveFitLibrary = FALSE), cvControl = list(), innerCvControl = list(), obsWeights = NULL, saveAll = TRUE, parallel = "seq", e... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/defaults.R
\name{default_fvars}
\alias{default_fvars}
\title{default fvars}
\usage{
default_fvars(object)
}
\arguments{
\item{object}{SummarizedExperiment}
}
\value{
string vector
}
\description{
default fvars
}
\examples{
if (require(autonom... | /autonomics.plot/man/default_fvars.Rd | no_license | bhagwataditya/autonomics0 | R | false | true | 442 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/defaults.R
\name{default_fvars}
\alias{default_fvars}
\title{default fvars}
\usage{
default_fvars(object)
}
\arguments{
\item{object}{SummarizedExperiment}
}
\value{
string vector
}
\description{
default fvars
}
\examples{
if (require(autonom... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/generics-getters.R
\name{getDefaultPackageData}
\alias{getDefaultPackageData}
\title{Get a list shared across modules within a same package}
\usage{
getDefaultPackageData()
}
\value{
A \code{\link[dipsaus]{fastmap2}} instance
}
\description{
... | /man/getDefaultPackageData.Rd | no_license | dipterix/ravecore | R | false | true | 535 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/generics-getters.R
\name{getDefaultPackageData}
\alias{getDefaultPackageData}
\title{Get a list shared across modules within a same package}
\usage{
getDefaultPackageData()
}
\value{
A \code{\link[dipsaus]{fastmap2}} instance
}
\description{
... |
library(RSurveillance)
### Name: n.tp
### Title: Sample size for true prevalence
### Aliases: n.tp
### Keywords: methods
### ** Examples
# examples for n.tp
n.tp(0.1, 0.9, 0.99, 0.05)
n.tp(0.1, 0.9, 0.99, 0.05, conf = 0.99)
n.tp(c(0.05, 0.1, 0.2, 0.3, 0.4, 0.5), 0.9, 0.99, 0.05)
n.tp(0.5, 0.9, 0.99, c(0.01, 0.02, 0... | /data/genthat_extracted_code/RSurveillance/examples/n.tp.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 339 | r | library(RSurveillance)
### Name: n.tp
### Title: Sample size for true prevalence
### Aliases: n.tp
### Keywords: methods
### ** Examples
# examples for n.tp
n.tp(0.1, 0.9, 0.99, 0.05)
n.tp(0.1, 0.9, 0.99, 0.05, conf = 0.99)
n.tp(c(0.05, 0.1, 0.2, 0.3, 0.4, 0.5), 0.9, 0.99, 0.05)
n.tp(0.5, 0.9, 0.99, c(0.01, 0.02, 0... |
library(mvtnorm)
library(fBasics)
set.seed(1)
N=1000
m=N/100
tt=seq(0,1, length.out = N) # USE M AS SAME NOTATION IN OUR LATEX FILE - M AND NOT H
t=vector(mode = "list", length = m) # TAKE SUBSET OF THE GRAM MATRIX
for (i in 1:m) {
t[[i]]=tt[1:(m*10*i)]
}
kernel_family=0
#KSE
Omega_t... | /R_code_Experiments/Ex_1_alg2_wrong.R | no_license | andreas-koukorinis/EMD_GP_Gareth_Marta_Dorota | R | false | false | 4,241 | r | library(mvtnorm)
library(fBasics)
set.seed(1)
N=1000
m=N/100
tt=seq(0,1, length.out = N) # USE M AS SAME NOTATION IN OUR LATEX FILE - M AND NOT H
t=vector(mode = "list", length = m) # TAKE SUBSET OF THE GRAM MATRIX
for (i in 1:m) {
t[[i]]=tt[1:(m*10*i)]
}
kernel_family=0
#KSE
Omega_t... |
library(smcsmcTools)
library(rjson)
library(GGally)
library(dplyr)
library(stringi)
library(scales)
library(ggalt)
config = fromJSON(file = "~/repos/eurasian-backmigration/analyses/sgdp_replication.json")
source = names_from_config(config$source) # from tools
source_strings = vapply(source, ids_to_names, character(1)... | /r/sgdp_subset_individual_mig.R | no_license | Chris1221/ancient_african_admixture | R | false | false | 3,526 | r | library(smcsmcTools)
library(rjson)
library(GGally)
library(dplyr)
library(stringi)
library(scales)
library(ggalt)
config = fromJSON(file = "~/repos/eurasian-backmigration/analyses/sgdp_replication.json")
source = names_from_config(config$source) # from tools
source_strings = vapply(source, ids_to_names, character(1)... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils.R
\name{.silenceF}
\alias{.silenceF}
\title{Silencing Functions}
\usage{
.silenceF(f, level = 7L)
}
\arguments{
\item{f}{function to silence}
\item{level}{a single numeric (integer) that indicates the silencing level, which encodes the... | /man/dot-silenceF.Rd | no_license | Bhanditz/pkgmaker | R | false | true | 1,818 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils.R
\name{.silenceF}
\alias{.silenceF}
\title{Silencing Functions}
\usage{
.silenceF(f, level = 7L)
}
\arguments{
\item{f}{function to silence}
\item{level}{a single numeric (integer) that indicates the silencing level, which encodes the... |
packages_to_install <- c(
"devtools",
"dplyr",
"ggplot2",
"knitr",
"magrittr",
"rmarkdown",
"tidyr"
)
install.packages(
packages_to_install,
dep = TRUE,
repos = "http://cran.rstudio.com"
)
| /r-packages.R | permissive | briandk/docker-academic-writing | R | false | false | 210 | r | packages_to_install <- c(
"devtools",
"dplyr",
"ggplot2",
"knitr",
"magrittr",
"rmarkdown",
"tidyr"
)
install.packages(
packages_to_install,
dep = TRUE,
repos = "http://cran.rstudio.com"
)
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/package.R
\docType{package}
\name{princurve-package}
\alias{princurve-package}
\alias{princurve}
\title{Fit a Principal Curve in Arbitrary Dimension}
\description{
Fit a principal curve which describes a smooth curve that passes through the \... | /man/princurve-package.Rd | no_license | rcannood/princurve | R | false | true | 1,088 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/package.R
\docType{package}
\name{princurve-package}
\alias{princurve-package}
\alias{princurve}
\title{Fit a Principal Curve in Arbitrary Dimension}
\description{
Fit a principal curve which describes a smooth curve that passes through the \... |
options(scipen = 999)
args <- commandArgs(trailingOnly = TRUE)
adds <- args[1]
removes <- args[2]
lookups <- args[3]
repetitions <- args[4]
a <- sample(1 : adds, adds)
b <- sample(a, removes)
if (repetitions == 0) {
c <- sample(a, lookups)
} else {
c <- sample(a, lookups, replace = TRUE)
}
write(c(0, adds, remo... | /Inputs/input_generator.R | no_license | AndreCascais/SelfBalancingTrees | R | false | false | 427 | r | options(scipen = 999)
args <- commandArgs(trailingOnly = TRUE)
adds <- args[1]
removes <- args[2]
lookups <- args[3]
repetitions <- args[4]
a <- sample(1 : adds, adds)
b <- sample(a, removes)
if (repetitions == 0) {
c <- sample(a, lookups)
} else {
c <- sample(a, lookups, replace = TRUE)
}
write(c(0, adds, remo... |
#!/usr/bin/env Rscript
#######
# LOG #
#######
log <- file(snakemake@log[[1]], open = "wt")
sink(log, type = "message")
sink(log, append = TRUE, type = "output")
#############
# LIBRARIES #
#############
library(data.table)
###########
# GLOBALS #
###########
interpro_res <- snakemake@input[["interpro_res"]]
blas... | /src/full_viral_table.R | no_license | sarahinwood/microctonus-viral | R | false | false | 498 | r | #!/usr/bin/env Rscript
#######
# LOG #
#######
log <- file(snakemake@log[[1]], open = "wt")
sink(log, type = "message")
sink(log, append = TRUE, type = "output")
#############
# LIBRARIES #
#############
library(data.table)
###########
# GLOBALS #
###########
interpro_res <- snakemake@input[["interpro_res"]]
blas... |
## The function takes two arguments:an outcome name (outcome) and the ranking of
## a hospital (num), and returns a 2-column data frame with the name of the hospital
## in each state that has the ranking specified in num
rankall <- function(outcome,num="best"){
data<-read.csv("outcome-of-care-measures.csv",string... | /C2Week4/rankall3.R | no_license | Shawvin/Data-Specilisation | R | false | false | 673 | r | ## The function takes two arguments:an outcome name (outcome) and the ranking of
## a hospital (num), and returns a 2-column data frame with the name of the hospital
## in each state that has the ranking specified in num
rankall <- function(outcome,num="best"){
data<-read.csv("outcome-of-care-measures.csv",string... |
# Load required packages
library(readxl)
library(tidyverse)
################ IMPORTING DATA ################
# Reading in CSV files
read_csv("data/mydata.csv")
# Read in and save data
mydata <- read_csv("data/mydata.csv")
# reading in an Excel file
excel_sheets("data/mydata.xlsx")
read_excel("data/mydata.xlsx", s... | /Internet/2018 - Intro to R Bootcamp/Module 02/script2.R | permissive | tarsoqueiroz/Rlang | R | false | false | 1,837 | r | # Load required packages
library(readxl)
library(tidyverse)
################ IMPORTING DATA ################
# Reading in CSV files
read_csv("data/mydata.csv")
# Read in and save data
mydata <- read_csv("data/mydata.csv")
# reading in an Excel file
excel_sheets("data/mydata.xlsx")
read_excel("data/mydata.xlsx", s... |
#
# samplesize_twofactorindindpower <- function(k1=3,k2=3,effectsize=0.8,sig_level = 0.05,power=0.8,forplot=FALSE,samplerange=NULL,effectsizerange=NULL){
k=k1*k2
library(pwr);library(jsonlite)
if(!forplot){
result = ceiling(pwr.anova.test(k = k, f = effectsize, sig.level = sig_level, power = power)$n)
}else... | /MetDADevelopmentR/rscript/samplesize_twofactorindindpower.R | no_license | slfan2013/MetDA-development | R | false | false | 1,137 | r | #
# samplesize_twofactorindindpower <- function(k1=3,k2=3,effectsize=0.8,sig_level = 0.05,power=0.8,forplot=FALSE,samplerange=NULL,effectsizerange=NULL){
k=k1*k2
library(pwr);library(jsonlite)
if(!forplot){
result = ceiling(pwr.anova.test(k = k, f = effectsize, sig.level = sig_level, power = power)$n)
}else... |
#' @title Generates a new set of knots for the following iteration
#' @description A sub-function of \code{\link{StagedChoiceSplineMix}}. This function generates a new set of knots for the following iteration. Please refer to Bruch et al. (in press) for the precise rule used.
#' @param num.knot See \code{\link{Staged... | /R/move.knot.r | no_license | cran/StagedChoiceSplineMix | R | false | false | 2,157 | r | #' @title Generates a new set of knots for the following iteration
#' @description A sub-function of \code{\link{StagedChoiceSplineMix}}. This function generates a new set of knots for the following iteration. Please refer to Bruch et al. (in press) for the precise rule used.
#' @param num.knot See \code{\link{Staged... |
##split test/train dataset for cross-validation, generating the input tables and lists of predictors for the models
set.seed(1234)
##function to generate the list of variables to include in an analysis
##vars = initial list of variables to include (some may be removed if there are few unique values)
##tab = table of d... | /machine_learning/1_format_model_inputs.R | permissive | CDCgov/Predicting_TB_cluster_growth | R | false | false | 5,011 | r | ##split test/train dataset for cross-validation, generating the input tables and lists of predictors for the models
set.seed(1234)
##function to generate the list of variables to include in an analysis
##vars = initial list of variables to include (some may be removed if there are few unique values)
##tab = table of d... |
#############################################################################
#
# XLConnect
# Copyright (C) 2010-2021 Mirai Solutions GmbH
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation... | /R/workbook.appendWorksheet.R | no_license | harisxue/xlconnect | R | false | false | 2,194 | r | #############################################################################
#
# XLConnect
# Copyright (C) 2010-2021 Mirai Solutions GmbH
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation... |
#' trigrame feature vector
#' @description This feature vector is 8000-dimentional feature vector wich is computed from tri-gram probability matrix
#'T obtained from PSSM Matrix.to achieve this purpose elements in three successive rows and arbitrary columns are multiplied
#'together then these results are added toget... | /R/AAtrigrame_pssm.R | no_license | minghao2016/PSSMCOOL-1 | R | false | false | 1,713 | r | #' trigrame feature vector
#' @description This feature vector is 8000-dimentional feature vector wich is computed from tri-gram probability matrix
#'T obtained from PSSM Matrix.to achieve this purpose elements in three successive rows and arbitrary columns are multiplied
#'together then these results are added toget... |
data <- read.table("foo.txt")
## Reading in Larger Datasets with read.table
initial <- read.table("datatable.txt", nrows = 100)
classes <- sapply(initial, class)
tabAll <- read.table("datatable.txt", colClasses = classes)
## dput-ting R Objects
y <- data.frame(a = 1, b = "a")
dput(y)
structure(list(a = 1,
... | /2. R Programming/ReadingData.R | no_license | shubhamjanhere/Coursera-Data-Science-Specialization | R | false | false | 1,117 | r | data <- read.table("foo.txt")
## Reading in Larger Datasets with read.table
initial <- read.table("datatable.txt", nrows = 100)
classes <- sapply(initial, class)
tabAll <- read.table("datatable.txt", colClasses = classes)
## dput-ting R Objects
y <- data.frame(a = 1, b = "a")
dput(y)
structure(list(a = 1,
... |
#' Select TextGrid Tier by its name
#'
#' This function takes a TextGrid and a name (character string), and returns the specified tier from that TextGrid
#' @param tg TextGrid data, returned from readTextGrid() function
#' @param tier_name character string. The name of the tier to retrive from TextGrid \code{tg}
#' @ex... | /R/getTierByName.R | no_license | fauxneticien/phonpack | R | false | false | 801 | r | #' Select TextGrid Tier by its name
#'
#' This function takes a TextGrid and a name (character string), and returns the specified tier from that TextGrid
#' @param tg TextGrid data, returned from readTextGrid() function
#' @param tier_name character string. The name of the tier to retrive from TextGrid \code{tg}
#' @ex... |
########################################################################################################################
## RnBSet-class.R
## created: 2012-04-06
## creator: Pavlo Lutsik
## ---------------------------------------------------------------------------------------------------------------------
## RnBSet cl... | /R/RnBSet-class.R | no_license | epigen/RnBeads | R | false | false | 94,066 | r | ########################################################################################################################
## RnBSet-class.R
## created: 2012-04-06
## creator: Pavlo Lutsik
## ---------------------------------------------------------------------------------------------------------------------
## RnBSet cl... |
args <- commandArgs(TRUE)
path_to_sig_file <- as.character(args[1])
path_to_file_bsmooth <- as.character(args[2])
path_to_file_dss <- as.character(args[3])
path_to_file_methylkit <- as.character(args[4])
path_to_file_metilene <- as.character(args[5])
path_to_file_rnbeads <- as.character(args[6])
sig <- read.t... | /01_scripts/additional_scripts/Evaluation/MethDiff.R | no_license | HeleneLuessem/Meta-Analysis-of-DMR-Finders | R | false | false | 4,857 | r | args <- commandArgs(TRUE)
path_to_sig_file <- as.character(args[1])
path_to_file_bsmooth <- as.character(args[2])
path_to_file_dss <- as.character(args[3])
path_to_file_methylkit <- as.character(args[4])
path_to_file_metilene <- as.character(args[5])
path_to_file_rnbeads <- as.character(args[6])
sig <- read.t... |
##########################################################
# A modification of ITCsegment package by Michele Dalponte
# Changes made by Tom Swinfield for the RSPB under funding from the Cambridge Conservation Initiative
# Collaborative Fund
##########################################################
# Changes made:
#... | /ITC segment update.R | no_license | swinersha/Tree-crown-segmentation | R | false | false | 15,833 | r | ##########################################################
# A modification of ITCsegment package by Michele Dalponte
# Changes made by Tom Swinfield for the RSPB under funding from the Cambridge Conservation Initiative
# Collaborative Fund
##########################################################
# Changes made:
#... |
PM25data <- readRDS("summarySCC_PM25.rds")
PM25data_BC_vehicle <- subset(PM25data, fips == "24510" & type == "ON-ROAD")
##use type ON-ROAD to define motor vehicle source
PM25data_BC_vehicle_totalbyyear <- tapply(PM25data_BC_vehicle$Emissions, PM25data_BC_vehicle$year, sum, na.rm=TRUE)
plot(names(PM25data_BC_veh... | /plot5.R | no_license | wenlytang/ExData_Plotting2 | R | false | false | 595 | r | PM25data <- readRDS("summarySCC_PM25.rds")
PM25data_BC_vehicle <- subset(PM25data, fips == "24510" & type == "ON-ROAD")
##use type ON-ROAD to define motor vehicle source
PM25data_BC_vehicle_totalbyyear <- tapply(PM25data_BC_vehicle$Emissions, PM25data_BC_vehicle$year, sum, na.rm=TRUE)
plot(names(PM25data_BC_veh... |
germline_patient_surv <- germline_patient_data %>% distinct(avatar_id, .keep_all = TRUE)
################################################################################### I ### PFS/OS hct date by HCT----
# From Dx
mysurv <- Surv(time = germline_patient_surv$month_at_progression_Dx, event = germline_patient_surv$Progr... | /R/7.2.Treatment survivals.R | no_license | GillisLabAtMoffitt/CHIP-Avatar | R | false | false | 70,488 | r | germline_patient_surv <- germline_patient_data %>% distinct(avatar_id, .keep_all = TRUE)
################################################################################### I ### PFS/OS hct date by HCT----
# From Dx
mysurv <- Surv(time = germline_patient_surv$month_at_progression_Dx, event = germline_patient_surv$Progr... |
context("nnm")
test_that("nnm.fit classification", {
x = iris[, 1:4]
y = iris[, 5]
mod = nnm.fit(x, y, list(Dense(4, 6), Dense(6, 3, Activation.Identity), Softmax))
expect_equal(length(mod$fitted), length(y))
})
test_that("nnm.fit regression", {
x = iris[, 1:3]
y = iris[, 4]
mod = nnm.fit(... | /tests/testthat/test_nnm.R | permissive | chuanwen/nnm | R | false | false | 1,901 | r | context("nnm")
test_that("nnm.fit classification", {
x = iris[, 1:4]
y = iris[, 5]
mod = nnm.fit(x, y, list(Dense(4, 6), Dense(6, 3, Activation.Identity), Softmax))
expect_equal(length(mod$fitted), length(y))
})
test_that("nnm.fit regression", {
x = iris[, 1:3]
y = iris[, 4]
mod = nnm.fit(... |
library(testthat)
library(recipes)
context("Matrix data types")
###################################################################
data(okc)
okc$diet <- as.factor(okc$diet)
okc$date <- as.Date(okc$date)
okc$location <- as.factor(okc$location)
okc_tr <- okc[1:400, ]
okc_te <- okc[(401:800), ]
###################... | /tests/testthat/test_matrix.R | no_license | EmilHvitfeldt/recipes | R | false | false | 1,827 | r | library(testthat)
library(recipes)
context("Matrix data types")
###################################################################
data(okc)
okc$diet <- as.factor(okc$diet)
okc$date <- as.Date(okc$date)
okc$location <- as.factor(okc$location)
okc_tr <- okc[1:400, ]
okc_te <- okc[(401:800), ]
###################... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/route53resolver_operations.R
\name{route53resolver_get_resolver_rule_policy}
\alias{route53resolver_get_resolver_rule_policy}
\title{Gets information about a resolver rule policy}
\usage{
route53resolver_get_resolver_rule_policy(Arn)
}
\argum... | /paws/man/route53resolver_get_resolver_rule_policy.Rd | permissive | johnnytommy/paws | R | false | true | 735 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/route53resolver_operations.R
\name{route53resolver_get_resolver_rule_policy}
\alias{route53resolver_get_resolver_rule_policy}
\title{Gets information about a resolver rule policy}
\usage{
route53resolver_get_resolver_rule_policy(Arn)
}
\argum... |
#' @import stats
#' @import ggplot2
precision = getFromNamespace("precision", "scales")
#' @importFrom magrittr %>%
#' @export
magrittr::`%>%`
#' @importFrom magrittr %<>%
#' @export
magrittr::`%<>%`
#' Parent Function: Power of a number.
#'
#' This is an internal function to generate another ones which will be
#' ... | /R/helpers.R | permissive | lfpdroubi/appraiseR | R | false | false | 9,515 | r | #' @import stats
#' @import ggplot2
precision = getFromNamespace("precision", "scales")
#' @importFrom magrittr %>%
#' @export
magrittr::`%>%`
#' @importFrom magrittr %<>%
#' @export
magrittr::`%<>%`
#' Parent Function: Power of a number.
#'
#' This is an internal function to generate another ones which will be
#' ... |
/models/KNN_model.R | no_license | Wynnlin329/R_EDA_minning | R | false | false | 725 | r | ||
#************** INTRODUCTION TO STATISTICS **********************************
#Types of data: Quantitative, Qualitative, Logical, Missing, Other types
#Quantitative: Discrete -- takes values in a finite and countable way.
# Continuous -- Takes values in an interval of numbers (decimal values).
#R comes... | /ch4_sumarize_data.R | no_license | hsimspace/statistics_with_r | R | false | false | 702 | r |
#************** INTRODUCTION TO STATISTICS **********************************
#Types of data: Quantitative, Qualitative, Logical, Missing, Other types
#Quantitative: Discrete -- takes values in a finite and countable way.
# Continuous -- Takes values in an interval of numbers (decimal values).
#R comes... |
<html>
<head>
<meta name="TextLength" content="SENT_NUM:4, WORD_NUM:92">
</head>
<body bgcolor="white">
<a href="#0" id="0">Tass said 748 of the injured had to be hospitalized and said a search was continuing for a police officer who vanished June 7.</a>
<a href="#1" id="1">It was the latest in a series of bloody civil... | /DUC-Dataset/Summary_p100_R/D105.AP900613-0195.html.R | no_license | Angela7126/SLNSumEval | R | false | false | 763 | r | <html>
<head>
<meta name="TextLength" content="SENT_NUM:4, WORD_NUM:92">
</head>
<body bgcolor="white">
<a href="#0" id="0">Tass said 748 of the injured had to be hospitalized and said a search was continuing for a police officer who vanished June 7.</a>
<a href="#1" id="1">It was the latest in a series of bloody civil... |
test_that("grade_code() - allow_partial_matching works 2 errors", {
expect_grade_code(
user_code = "purrr::insistently(mean,quie = TRUE,rat = rate_backoff())",
solution_code = "purrr::insistently(mean,quiet = TRUE,rate = rate_backoff())",
is_correct = TRUE
)
expect_grade_code(
user_code = "purrr::... | /tests/testthat/test-allow_partial_matching.R | permissive | rstudio/gradethis | R | false | false | 11,263 | r | test_that("grade_code() - allow_partial_matching works 2 errors", {
expect_grade_code(
user_code = "purrr::insistently(mean,quie = TRUE,rat = rate_backoff())",
solution_code = "purrr::insistently(mean,quiet = TRUE,rate = rate_backoff())",
is_correct = TRUE
)
expect_grade_code(
user_code = "purrr::... |
context("get_followers")
test_that("get_followers returns data frame with user_id", {
skip_on_cran()
skip_if_offline()
token <- readRDS("twitter_tokens")
rl <- rate_limit(token, "get_followers")
if (rl$remaining > 1) {
f <- get_followers("HillaryClinton", n = 10000, token = token)
expect_true(i... | /tests/testthat/test_get_followers.R | no_license | zzqqzzqqzz/rtweet | R | false | false | 601 | r | context("get_followers")
test_that("get_followers returns data frame with user_id", {
skip_on_cran()
skip_if_offline()
token <- readRDS("twitter_tokens")
rl <- rate_limit(token, "get_followers")
if (rl$remaining > 1) {
f <- get_followers("HillaryClinton", n = 10000, token = token)
expect_true(i... |
rm(list = ls())
library(tidyverse)
library(foreach)
library(matrixStats)
library(here)
folder_path <- here("data/PO4Ca_GT/umbrella/10blocks/")
file_name <- "PO4Ca_GT"
n_block <- 10
all_pmfs <-
foreach( i = 0:(n_block-1), .combine = "c") %do% {
pmf_file <- paste(folder_path, "pmf", i, ".xvg", sep = "")
all_c... | /utilities/get_PMF/block_average_PO4Ca_GT.R | no_license | andy90/DNA_simulation | R | false | false | 1,745 | r | rm(list = ls())
library(tidyverse)
library(foreach)
library(matrixStats)
library(here)
folder_path <- here("data/PO4Ca_GT/umbrella/10blocks/")
file_name <- "PO4Ca_GT"
n_block <- 10
all_pmfs <-
foreach( i = 0:(n_block-1), .combine = "c") %do% {
pmf_file <- paste(folder_path, "pmf", i, ".xvg", sep = "")
all_c... |
#' @title Create table 1, part 1 from the credit union publication
#'
#' @description Creates Table 1, part 1 from the \href{https://www.bankofengland.co.uk/news?NewsTypes=571948d14c6943f7b5b7748ad80bef29&Direction=Upcoming}{Credit Union Quarterly Release}.
#'
#' @details \code{table_1} takes as input a standardise... | /table_1_part_1.R | no_license | JoshuaAllenBoE/CreditUnionRAP | R | false | false | 1,881 | r | #' @title Create table 1, part 1 from the credit union publication
#'
#' @description Creates Table 1, part 1 from the \href{https://www.bankofengland.co.uk/news?NewsTypes=571948d14c6943f7b5b7748ad80bef29&Direction=Upcoming}{Credit Union Quarterly Release}.
#'
#' @details \code{table_1} takes as input a standardise... |
### NOTE TO USERS ###
#' The following code uses parellel computation with up to 30 cores being used at once.
#' Parallelization was completed using the mclapply function. To run this script locally,
#' replace mclapply with lapply and remove the mc.cores parameter. This quantile
#' estimator should be able to run lo... | /analyses_scripts/unimodal_quantile_estimates.R | no_license | mbelitz/belitz_etal_phenometrics | R | false | false | 39,146 | r | ### NOTE TO USERS ###
#' The following code uses parellel computation with up to 30 cores being used at once.
#' Parallelization was completed using the mclapply function. To run this script locally,
#' replace mclapply with lapply and remove the mc.cores parameter. This quantile
#' estimator should be able to run lo... |
# Check if both data exist. If not, load the data.
if (!"data" %in% ls()) {
pmData <- readRDS("./data/summarySCC_PM25.rds")
}
if (!"data" %in% ls()) {
classData <- readRDS("./data/Source_Classification_Code.rds")
}
#plt the data
par("mar"=c(5.1, 4.5, 4.1, 2.1))
png(filename = "plot4.png",
width = ... | /plot4.R | no_license | ez3804/ExData_Prj2 | R | false | false | 762 | r | # Check if both data exist. If not, load the data.
if (!"data" %in% ls()) {
pmData <- readRDS("./data/summarySCC_PM25.rds")
}
if (!"data" %in% ls()) {
classData <- readRDS("./data/Source_Classification_Code.rds")
}
#plt the data
par("mar"=c(5.1, 4.5, 4.1, 2.1))
png(filename = "plot4.png",
width = ... |
# Run this on Domino ####
source('/mnt/simulator/sim_phenos.R')
source('/mnt/simulator/create_cross_design.R')
source('/mnt/simulator/make_crosses.R')
source('/mnt/simulator/calc_TGV.R')
source('/mnt/simulator/extract_selections.R')
source('/mnt/simulator/create_map.R')
source('/mnt/simulator/create_parents.R')
source(... | /replicate_GF_study/volume.R | permissive | arfesta/SimBreeder_Project | R | false | false | 5,495 | r | # Run this on Domino ####
source('/mnt/simulator/sim_phenos.R')
source('/mnt/simulator/create_cross_design.R')
source('/mnt/simulator/make_crosses.R')
source('/mnt/simulator/calc_TGV.R')
source('/mnt/simulator/extract_selections.R')
source('/mnt/simulator/create_map.R')
source('/mnt/simulator/create_parents.R')
source(... |
best <- function(state, outcome) {
##Read outcome data
data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
fulldata <- as.data.frame(cbind(data[, 2], ##hospital
data[, 7], ##state
data[, 11], ##heart attack
... | /best.R | no_license | abheekbiswas/ProgrammingAssignment3 | R | false | false | 1,258 | r | best <- function(state, outcome) {
##Read outcome data
data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
fulldata <- as.data.frame(cbind(data[, 2], ##hospital
data[, 7], ##state
data[, 11], ##heart attack
... |
library(ggplot2)
library(dplyr)
library(gridExtra)
library(timetk)
### Plot time series for variables
load('data/FL.Rda')
fl = FL %>%
filter(policydate < as.Date("2019-08-01")) %>%
summarise_by_time(.date_var = policydate, .by= "year",
cost = mean(policycost),
num = ... | /not used/timeser_Onestates.R | no_license | LenaChretien/National_flood_insurance | R | false | false | 6,463 | r | library(ggplot2)
library(dplyr)
library(gridExtra)
library(timetk)
### Plot time series for variables
load('data/FL.Rda')
fl = FL %>%
filter(policydate < as.Date("2019-08-01")) %>%
summarise_by_time(.date_var = policydate, .by= "year",
cost = mean(policycost),
num = ... |
/semaforos.R | permissive | fagnersutel/pontoscriticos | R | false | false | 2,276 | r | ||
#Week 2 Quiz q5
file_url <- "https://d396qusza40orc.cloudfront.net/getdata%2Fwksst8110.for"
df <- read.fwf(file_url, skip = 4, widths = c(12, 7, 4, 9, 4, 9, 4, 9, 4))
print(sum(df$V4))
| /Getting_and_Cleaning_Data/W2_Quiz_q5.R | no_license | Mjvolk3/datasciencecoursera | R | false | false | 185 | r | #Week 2 Quiz q5
file_url <- "https://d396qusza40orc.cloudfront.net/getdata%2Fwksst8110.for"
df <- read.fwf(file_url, skip = 4, widths = c(12, 7, 4, 9, 4, 9, 4, 9, 4))
print(sum(df$V4))
|
RNGkind(sample.kind="Rounding")
library(bhpm)
set.seed(14258)
######################### All events, Severity 1, Model BB_dependent #####################
print("######################### All events, Severity 1, Model BB level 1 #####################")
data(demo.cluster.data)
set.seed(9019)
raw = bhpm.pm(demo.cluster.... | /test/bhpm.pm/single_chain/default_parameters/test/run.r | no_license | rcarragh/bhpm | R | false | false | 844 | r | RNGkind(sample.kind="Rounding")
library(bhpm)
set.seed(14258)
######################### All events, Severity 1, Model BB_dependent #####################
print("######################### All events, Severity 1, Model BB level 1 #####################")
data(demo.cluster.data)
set.seed(9019)
raw = bhpm.pm(demo.cluster.... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tar_watch_ui.R
\name{tar_watch_ui}
\alias{tar_watch_ui}
\title{Shiny module UI for tar_watch()}
\usage{
tar_watch_ui(
id,
label = "tar_watch_label",
seconds = 10,
seconds_min = 1,
seconds_max = 60,
seconds_step = 1,
targets_only... | /man/tar_watch_ui.Rd | permissive | ropensci/targets | R | false | true | 3,479 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tar_watch_ui.R
\name{tar_watch_ui}
\alias{tar_watch_ui}
\title{Shiny module UI for tar_watch()}
\usage{
tar_watch_ui(
id,
label = "tar_watch_label",
seconds = 10,
seconds_min = 1,
seconds_max = 60,
seconds_step = 1,
targets_only... |
#Run the script with the associated metabolite file.
#Rscript compare_metab.R MetabTable_ForComparison.csv Results_features.txt
args<-commandArgs(TRUE)
data<-read.table(args[1],sep=",",row.names=1,header=TRUE)
metab_pos<-grep("X",names(data))
results_data<-as.data.frame(matrix(NA,length(metab_pos),12))
for(i in 1:... | /compare_metab.R | permissive | mccall-lab-OU/GI-tract-paper | R | false | false | 1,127 | r | #Run the script with the associated metabolite file.
#Rscript compare_metab.R MetabTable_ForComparison.csv Results_features.txt
args<-commandArgs(TRUE)
data<-read.table(args[1],sep=",",row.names=1,header=TRUE)
metab_pos<-grep("X",names(data))
results_data<-as.data.frame(matrix(NA,length(metab_pos),12))
for(i in 1:... |
# 9 April 2020—Lab 13 "Occupancy ####
library(unmarked)
library(MuMIn)
library(ggplot2)
# Single season occupancy ####
badger <- read.csv("badger_occupancy_scotland.csv", header = TRUE)
head(badger)
badger.o <- unmarkedFrameOccu(y = badger[,4:25],
siteCovs = badger[,c(26,27,32,41,46)])
plot(badger.o)
pd... | /9_April_Occupancy.R | no_license | masond-UF/iQAAP | R | false | false | 4,924 | r | # 9 April 2020—Lab 13 "Occupancy ####
library(unmarked)
library(MuMIn)
library(ggplot2)
# Single season occupancy ####
badger <- read.csv("badger_occupancy_scotland.csv", header = TRUE)
head(badger)
badger.o <- unmarkedFrameOccu(y = badger[,4:25],
siteCovs = badger[,c(26,27,32,41,46)])
plot(badger.o)
pd... |
# Exercise 1: Creating and Indexing Vectors
# Create a vector `first.ten` that has the values 10 through 20 in it (using the : operator)
first.ten <- 10:20
# Create a vector `next.ten` that has the values 21 through 30 in it (using the seq operator)
next.ten <- seq(21:30)
# Create a vector `all.numbers` by combining... | /exercise-1/exercise.R | permissive | kevinwork98/ch7-vectors | R | false | false | 985 | r | # Exercise 1: Creating and Indexing Vectors
# Create a vector `first.ten` that has the values 10 through 20 in it (using the : operator)
first.ten <- 10:20
# Create a vector `next.ten` that has the values 21 through 30 in it (using the seq operator)
next.ten <- seq(21:30)
# Create a vector `all.numbers` by combining... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Met_MatH.R
\name{WH.var.covar}
\alias{WH.var.covar}
\alias{WH.var.covar,MatH-method}
\title{Method WH.var.covar}
\usage{
WH.var.covar(object, ...)
\S4method{WH.var.covar}{MatH}(object, w = numeric(0))
}
\arguments{
\item{object}{... | /man/WH.var.covar-methods.Rd | no_license | cran/HistDAWass | R | false | true | 1,183 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Met_MatH.R
\name{WH.var.covar}
\alias{WH.var.covar}
\alias{WH.var.covar,MatH-method}
\title{Method WH.var.covar}
\usage{
WH.var.covar(object, ...)
\S4method{WH.var.covar}{MatH}(object, w = numeric(0))
}
\arguments{
\item{object}{... |
### get parameters
args = commandArgs(trailingOnly=TRUE)
index_set_inputfile = args[1]
regin_index_inputfile = args[2]
regin_signal_inputfile = args[3]
index_set_all_heatmap = args[4]
index_set_thresh_heatmap = args[5]
index_all_heatmap = args[6]
### read index set signal matrix
read_enriched_index_set_matrix = func... | /bin/index_calling.R | no_license | guanjue/index_caller | R | false | false | 13,686 | r | ### get parameters
args = commandArgs(trailingOnly=TRUE)
index_set_inputfile = args[1]
regin_index_inputfile = args[2]
regin_signal_inputfile = args[3]
index_set_all_heatmap = args[4]
index_set_thresh_heatmap = args[5]
index_all_heatmap = args[6]
### read index set signal matrix
read_enriched_index_set_matrix = func... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fn.lambda.R
\name{fn.lambda}
\alias{fn.lambda}
\title{Calculate recruitment bias based on environmental filtering}
\usage{
fn.lambda(trait.optimum, niche.breadth, Ef, Ef.specificity)
}
\arguments{
\item{trait.optimum}{Optimum value for a give... | /man/fn.lambda.Rd | no_license | sokole/MCSim | R | false | true | 1,195 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fn.lambda.R
\name{fn.lambda}
\alias{fn.lambda}
\title{Calculate recruitment bias based on environmental filtering}
\usage{
fn.lambda(trait.optimum, niche.breadth, Ef, Ef.specificity)
}
\arguments{
\item{trait.optimum}{Optimum value for a give... |
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