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 |
|---|---|---|---|---|---|---|---|---|---|
## MannWhitney_SplitYearSensitivity.R
# This script will test the sensitivity of the Mann-Whitney results to the year chosen for the split.
source(file.path("code", "paths+packages.R"))
## load data
gage_regions <-
readr::read_csv(file.path("results", "00_SelectGagesForAnalysis_GageRegions.csv"))
gage_sample_annu... | /figures_manuscript/MannWhitney_SplitYearSensitivity.R | no_license | dry-rivers-rcn/IntermittencyTrends | R | false | false | 7,667 | r | ## MannWhitney_SplitYearSensitivity.R
# This script will test the sensitivity of the Mann-Whitney results to the year chosen for the split.
source(file.path("code", "paths+packages.R"))
## load data
gage_regions <-
readr::read_csv(file.path("results", "00_SelectGagesForAnalysis_GageRegions.csv"))
gage_sample_annu... |
\name{CPTtools-package}
\alias{CPTtools-package}
\alias{CPTtools}
\docType{package}
\title{
\packageTitle{CPTtools}
}
\description{
\packageDescription{CPTtools}
}
\details{
The DESCRIPTION file:
\packageDESCRIPTION{CPTtools}
CPTtools is a collection of various bits of R code useful for processing
Bayes net output. ... | /man/CPTtools-package.Rd | permissive | erge324/CPTtools | R | false | false | 16,265 | rd | \name{CPTtools-package}
\alias{CPTtools-package}
\alias{CPTtools}
\docType{package}
\title{
\packageTitle{CPTtools}
}
\description{
\packageDescription{CPTtools}
}
\details{
The DESCRIPTION file:
\packageDESCRIPTION{CPTtools}
CPTtools is a collection of various bits of R code useful for processing
Bayes net output. ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/datasets.R
\name{data_path}
\alias{data_path}
\title{Represents a path to data in a datastore.}
\usage{
data_path(datastore, path_on_datastore = NULL, name = NULL)
}
\arguments{
\item{datastore}{The Datastore to reference.}
\item{path_on_dat... | /man/data_path.Rd | permissive | revodavid/azureml-sdk-for-r | R | false | true | 1,314 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/datasets.R
\name{data_path}
\alias{data_path}
\title{Represents a path to data in a datastore.}
\usage{
data_path(datastore, path_on_datastore = NULL, name = NULL)
}
\arguments{
\item{datastore}{The Datastore to reference.}
\item{path_on_dat... |
# nocov - compat-purrr (last updated: rlang 0.0.0.9007)
# This file serves as a reference for compatibility functions for
# purrr. They are not drop-in replacements but allow a similar style
# of programming. This is useful in cases where purrr is too heavy a
# package to depend on. Please find the most recent version... | /R/compat-purrr.R | no_license | krlmlr/brushthat | R | false | false | 3,736 | r | # nocov - compat-purrr (last updated: rlang 0.0.0.9007)
# This file serves as a reference for compatibility functions for
# purrr. They are not drop-in replacements but allow a similar style
# of programming. This is useful in cases where purrr is too heavy a
# package to depend on. Please find the most recent version... |
gammaresiduals <-
function(Y,X,model){
Y <- as.matrix(Y)
residuals <- model$residuals
variance <- model$variance
phi <- model$precision
yestimado <- model$fitted.values
#Absolute residuals
rabs<-abs(residuals)
#Standardized Weighted Residual 1
rp<-residuals/sqrt(variance)
#... | /R/gammaresiduals.R | no_license | cran/Bayesiangammareg | R | false | false | 688 | r | gammaresiduals <-
function(Y,X,model){
Y <- as.matrix(Y)
residuals <- model$residuals
variance <- model$variance
phi <- model$precision
yestimado <- model$fitted.values
#Absolute residuals
rabs<-abs(residuals)
#Standardized Weighted Residual 1
rp<-residuals/sqrt(variance)
#... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Package.R
\docType{package}
\name{PLEFinal-package}
\alias{PLEFinal}
\alias{PLEFinal-package}
\title{PLEFinal: A Package Skeleton for Comparative Effectiveness Studies}
\description{
A skeleton package, to be used as a starting point ... | /PLEFinal/man/SkeletonComparativeEffectStudy-package.Rd | permissive | jennifercelane/PLEMSKAI_working | R | false | true | 390 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Package.R
\docType{package}
\name{PLEFinal-package}
\alias{PLEFinal}
\alias{PLEFinal-package}
\title{PLEFinal: A Package Skeleton for Comparative Effectiveness Studies}
\description{
A skeleton package, to be used as a starting point ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get.IDR.discrete.R
\name{get.IDR.discrete}
\alias{get.IDR.discrete}
\title{compute IDR for discrete categories}
\usage{
get.IDR.discrete(idr, cat.counts)
}
\arguments{
\item{idr}{local idr for each category.}
\item{cat.counts}{the... | /man/get.IDR.discrete.Rd | no_license | TaoYang-dev/gIDR | R | false | true | 592 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get.IDR.discrete.R
\name{get.IDR.discrete}
\alias{get.IDR.discrete}
\title{compute IDR for discrete categories}
\usage{
get.IDR.discrete(idr, cat.counts)
}
\arguments{
\item{idr}{local idr for each category.}
\item{cat.counts}{the... |
## Packages used
library(dplyr); library(tidyr)
## Download data
if(!file.exists("./data")){
dir.create("./data")
fileUrl <- "https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip"
download.file(fileUrl, destfile = "./data/zip.zip", method = "curl")
rm(f... | /run_analysis.R | no_license | mattayes/samsung-har | R | false | false | 3,177 | r | ## Packages used
library(dplyr); library(tidyr)
## Download data
if(!file.exists("./data")){
dir.create("./data")
fileUrl <- "https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip"
download.file(fileUrl, destfile = "./data/zip.zip", method = "curl")
rm(f... |
library(tidyverse)
library(scales)
library(Cairo)
theme_set(theme_classic())
Ex_1 <- tribble(
~Tier, ~Number_Account, ~Percentage_Accounts, ~Revenue_M, ~Percentage_Revenue,
'A', 77, 7.08, 4.68, 25,
'A+', 19, 1.75, 3.93, 21,
'B', 338, 31.07, 5.98, 32,
'C', 425, 39.06, 2.81, 15,
'D', 24, 2.21, 0.37, 2
) %>%... | /Storytelling_with_Data/2019_10_SWD_Challenge.R | no_license | jorgel-mendes/Behold-the-Vision | R | false | false | 2,875 | r | library(tidyverse)
library(scales)
library(Cairo)
theme_set(theme_classic())
Ex_1 <- tribble(
~Tier, ~Number_Account, ~Percentage_Accounts, ~Revenue_M, ~Percentage_Revenue,
'A', 77, 7.08, 4.68, 25,
'A+', 19, 1.75, 3.93, 21,
'B', 338, 31.07, 5.98, 32,
'C', 425, 39.06, 2.81, 15,
'D', 24, 2.21, 0.37, 2
) %>%... |
# scalar(스칼라): 한개의 값이 저장된 객체(object, 변수 variable).
# vector(벡터): 한가지 타입(유형)의 여러개의 값이 1차원으로 저장된 객체.
# scalar의 예
x <- 100 # x: 숫자 한개를 저장하고 있는 scalar
name <- '오쌤' # name: 문자열 한개를 저장하고 있는 scalar
name
# R에서는 문자열을 작은따옴표('') 또는 큰따옴표("")로 묶을 수 있음.
# (비교) SQL에서는 문자열을 사용할 때 작은따옴표만 사용해야 함.
is_big <- TRUE # 논릿값(logi... | /r02_scalar_vector.R | no_license | seanhong7777/R | R | false | false | 3,065 | r | # scalar(스칼라): 한개의 값이 저장된 객체(object, 변수 variable).
# vector(벡터): 한가지 타입(유형)의 여러개의 값이 1차원으로 저장된 객체.
# scalar의 예
x <- 100 # x: 숫자 한개를 저장하고 있는 scalar
name <- '오쌤' # name: 문자열 한개를 저장하고 있는 scalar
name
# R에서는 문자열을 작은따옴표('') 또는 큰따옴표("")로 묶을 수 있음.
# (비교) SQL에서는 문자열을 사용할 때 작은따옴표만 사용해야 함.
is_big <- TRUE # 논릿값(logi... |
#html_session_try adds:
#1.auto retry functionality using exponantial delay(2s,4s,8s,16s etc)
#2.use tryCatch to create robust scraper, any network issues or error will not break the script. It's safe to run it in loops
#3.keep track of unsuccessful request(including both error and warning).Conditions of failed request... | /R Projects/function/html_session_try.R | no_license | yusuzech/web-scraping-projects | R | false | false | 1,613 | r | #html_session_try adds:
#1.auto retry functionality using exponantial delay(2s,4s,8s,16s etc)
#2.use tryCatch to create robust scraper, any network issues or error will not break the script. It's safe to run it in loops
#3.keep track of unsuccessful request(including both error and warning).Conditions of failed request... |
# cmd_args=commandArgs(TRUE)
#
# ngenecl <- as.numeric(cmd_args[1]) # cells per cell type
# out <- cmd_args[2]
source("/proj/milovelab/mu/SC-ASE/simulation/cluster.R")
source("/proj/milovelab/mu/SC-ASE/simulation/fusedlasso.R")
library("smurf")
library(emdbook)
library(mclust)
library(pbapply)
library(aricode)
librar... | /simulation/sim2.R | no_license | Wancen/SC-ASE | R | false | false | 3,866 | r | # cmd_args=commandArgs(TRUE)
#
# ngenecl <- as.numeric(cmd_args[1]) # cells per cell type
# out <- cmd_args[2]
source("/proj/milovelab/mu/SC-ASE/simulation/cluster.R")
source("/proj/milovelab/mu/SC-ASE/simulation/fusedlasso.R")
library("smurf")
library(emdbook)
library(mclust)
library(pbapply)
library(aricode)
librar... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/currentarrows.R
\name{currentarrows}
\alias{currentarrows}
\title{Plot arrows and segments showing the size and direction of currents.}
\usage{
currentarrows(
data,
maxsize = 0.5,
maxn,
col = "blue",
lwd = 2,
arrowsize = 0.2,
ce... | /man/currentarrows.Rd | no_license | Hafro/geo | R | false | true | 986 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/currentarrows.R
\name{currentarrows}
\alias{currentarrows}
\title{Plot arrows and segments showing the size and direction of currents.}
\usage{
currentarrows(
data,
maxsize = 0.5,
maxn,
col = "blue",
lwd = 2,
arrowsize = 0.2,
ce... |
## This function creates a special "matrix" object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
}
## This function computes the inverse of the special "matrix" returned by makeCacheMatrix above. If the inverse has already been calculated (and the matrix has not changed), then the cacheso... | /cachematrix.R | no_license | datatool/ProgrammingAssignment2 | R | false | false | 619 | r | ## This function creates a special "matrix" object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
}
## This function computes the inverse of the special "matrix" returned by makeCacheMatrix above. If the inverse has already been calculated (and the matrix has not changed), then the cacheso... |
#!/usr/bin/Rscript
# Daily Pick
##############
#
# Standalone script intended to be run by Cron job to report daily picks.
#
delta=30
theDate=as.Date(Sys.time())
#Share Select
setwd("/home/raffles/Raffles/")
source("Quantlib.R")
setwd("./Data/")
loadLocalData()
#Loads basic libraries and sets up required environme... | /DailyPick.R.save | no_license | piratesjustarr/Raffles | R | false | false | 1,755 | save | #!/usr/bin/Rscript
# Daily Pick
##############
#
# Standalone script intended to be run by Cron job to report daily picks.
#
delta=30
theDate=as.Date(Sys.time())
#Share Select
setwd("/home/raffles/Raffles/")
source("Quantlib.R")
setwd("./Data/")
loadLocalData()
#Loads basic libraries and sets up required environme... |
testlist <- list(scale = 1.17613105186789e-309, shape = -2.95612684604669e-196)
result <- do.call(bama:::rand_igamma,testlist)
str(result) | /bama/inst/testfiles/rand_igamma/AFL_rand_igamma/rand_igamma_valgrind_files/1615926417-test.R | no_license | akhikolla/updatedatatype-list1 | R | false | false | 138 | r | testlist <- list(scale = 1.17613105186789e-309, shape = -2.95612684604669e-196)
result <- do.call(bama:::rand_igamma,testlist)
str(result) |
#代码更适合批量化和自动化，鼠标是替代不了的 | /excel案例.R | no_license | liuiscoding/R_learn | R | false | false | 64 | r | #代码更适合批量化和自动化，鼠标是替代不了的 |
gap.barplot<-function (y,gap,xaxlab,xtics,yaxlab,ytics,xlim=NA,ylim=NA,
xlab=NULL,ylab=NULL,horiz=FALSE,col=NULL,...) {
if (missing(y)) stop("y values required")
if(missing(xtics)) xtics <- 1:length(y)
if (missing(gap)) stop("gap must be specified")
if (is.null(ylab)) ylab <- deparse(substitute(y))
if (is.n... | /primeiroProjetoR/plotrix/R/gap.barplot.R | no_license | bernardomsvieira/Rproject | R | false | false | 2,321 | r | gap.barplot<-function (y,gap,xaxlab,xtics,yaxlab,ytics,xlim=NA,ylim=NA,
xlab=NULL,ylab=NULL,horiz=FALSE,col=NULL,...) {
if (missing(y)) stop("y values required")
if(missing(xtics)) xtics <- 1:length(y)
if (missing(gap)) stop("gap must be specified")
if (is.null(ylab)) ylab <- deparse(substitute(y))
if (is.n... |
library(multistate)
### Name: sm4rs
### Title: 4-State Relative Survival Semi-Markov Model with Additive Risks
### Aliases: sm4rs
### Keywords: semi-Markov relative survival
### ** Examples
# import the observed data
# (X=1 corresponds to initial state with a functioning graft, X=2 to acute rejection episode,
# X=... | /data/genthat_extracted_code/multistate/examples/sm4rs.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 1,506 | r | library(multistate)
### Name: sm4rs
### Title: 4-State Relative Survival Semi-Markov Model with Additive Risks
### Aliases: sm4rs
### Keywords: semi-Markov relative survival
### ** Examples
# import the observed data
# (X=1 corresponds to initial state with a functioning graft, X=2 to acute rejection episode,
# X=... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sw.R
\name{T68fromT90}
\alias{T68fromT90}
\title{Convert from ITS-90 to IPTS-68 temperature}
\usage{
T68fromT90(temperature)
}
\arguments{
\item{temperature}{Vector of temperatures expressed in the ITS-90 scale.}
}
\value{
Temperature express... | /pkgs/oce/man/T68fromT90.Rd | no_license | vaguiar/EDAV_Project_2017 | R | false | true | 2,283 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sw.R
\name{T68fromT90}
\alias{T68fromT90}
\title{Convert from ITS-90 to IPTS-68 temperature}
\usage{
T68fromT90(temperature)
}
\arguments{
\item{temperature}{Vector of temperatures expressed in the ITS-90 scale.}
}
\value{
Temperature express... |
setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../h2o-runit.R')
test.pub_697_exec_bad_key_name <- function() {
prostatePath = locate("smalldata/prostate/prostate.csv")
prostate.hex = h2o.importFile(path = prostatePath, destination_frame = "prostate.hex")
prostate.local = as.data.frame... | /h2o-r/tests/testdir_jira/runit_pub_697_exec_bad_key_name.R | permissive | tamseo/h2o-3 | R | false | false | 711 | r | setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source('../h2o-runit.R')
test.pub_697_exec_bad_key_name <- function() {
prostatePath = locate("smalldata/prostate/prostate.csv")
prostate.hex = h2o.importFile(path = prostatePath, destination_frame = "prostate.hex")
prostate.local = as.data.frame... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ParetoShrinkage.R
\name{R2_Wherry}
\alias{R2_Wherry}
\title{R2_Wherry function}
\usage{
R2_Wherry(N, p, R2)
}
\arguments{
\item{N}{Sample size}
\item{p}{number of predictors}
\item{R2}{R-squared}
}
\value{
R2_W formula-adjus... | /man/R2_Wherry.Rd | no_license | Diversity-ParetoOptimal/ParetoR | R | false | true | 613 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ParetoShrinkage.R
\name{R2_Wherry}
\alias{R2_Wherry}
\title{R2_Wherry function}
\usage{
R2_Wherry(N, p, R2)
}
\arguments{
\item{N}{Sample size}
\item{p}{number of predictors}
\item{R2}{R-squared}
}
\value{
R2_W formula-adjus... |
###############################################################################
# #
# execute exp3_bayes_t_priors.R #
# #
###############################################################################
setwd("Documents/wiskunde/2017-2018/bachelor_project/R/... | /R/exp3_bayes_tpriors.R | no_license | StudentThom/handin_bachelor_project | R | false | false | 3,190 | r | ###############################################################################
# #
# execute exp3_bayes_t_priors.R #
# #
###############################################################################
setwd("Documents/wiskunde/2017-2018/bachelor_project/R/... |
#######################
### Meta-Analyse: Korrelationen
# von Julien P. Irmer
## Vorbereitung
library(metafor)
## Übersicht über den Datensatz verschaffen
head(dat.molloy2014)
summary(dat.molloy2014$ri)
## Grafische Veranschaulichung der Beziehung zwischen der Medikamenteneinnahme und der Gewissenhaftigkeit
boxplot... | /content/post/KliPPs_MSc5a_R_Files/8_meta-analyse_korrelationen_RCode.R | no_license | martscht/projekte | R | false | false | 2,090 | r | #######################
### Meta-Analyse: Korrelationen
# von Julien P. Irmer
## Vorbereitung
library(metafor)
## Übersicht über den Datensatz verschaffen
head(dat.molloy2014)
summary(dat.molloy2014$ri)
## Grafische Veranschaulichung der Beziehung zwischen der Medikamenteneinnahme und der Gewissenhaftigkeit
boxplot... |
#######################################################################################
#
# This file is Question5.R
# The purpose is to address the fifth question on the merged data.
# "Cut the GDP rankings into 5 separate quantile groups."
# "Make a table versus Income Group."
# "How man... | /Analysis/Question5.R | no_license | bgobran/CaseStudy1FinalVersion | R | false | false | 3,259 | r | #######################################################################################
#
# This file is Question5.R
# The purpose is to address the fifth question on the merged data.
# "Cut the GDP rankings into 5 separate quantile groups."
# "Make a table versus Income Group."
# "How man... |
#' Print DataM Object
#'
#' Modifies the "print" function to take objects of class \code{DataM} (or any of its subclasses) and print out a matrix where the first column is the dependent variable and the remaining columns are the independent variables.
#'
#' @param DataM An object of class DataM
#'
#' @author Thomas... | /MyPackage/R/print-mod.R | no_license | thomasscarroll89/RPackageProblemSet | R | false | false | 573 | r | #' Print DataM Object
#'
#' Modifies the "print" function to take objects of class \code{DataM} (or any of its subclasses) and print out a matrix where the first column is the dependent variable and the remaining columns are the independent variables.
#'
#' @param DataM An object of class DataM
#'
#' @author Thomas... |
testlist <- list(data = structure(c(6.53867576132537e+286, 6.53867576126997e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53... | /biwavelet/inst/testfiles/rcpp_row_quantile/libFuzzer_rcpp_row_quantile/rcpp_row_quantile_valgrind_files/1610554326-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 713 | r | testlist <- list(data = structure(c(6.53867576132537e+286, 6.53867576126997e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53867576132537e+286, 6.53... |
#Read the two files
NEI <- readRDS("summarySCC_PM25.rds")
SCC <- readRDS("Source_Classification_Code.rds")
str(NEI)
library(ggplot2)
library(plyr)
#Retain just the Baltimore City data
NEI_Baltimore <- NEI[NEI$fips == "24510",]
#Convert type variable to a factor
NEI_Baltimore$type <- as.factor(NEI_Baltimore$type)
#Ag... | /Exploratory_Data_Analysis_Assignment2/plot3.R | no_license | sharathlives/JohnHopkins_Coursera_Exploratory_Data_Analysis | R | false | false | 905 | r | #Read the two files
NEI <- readRDS("summarySCC_PM25.rds")
SCC <- readRDS("Source_Classification_Code.rds")
str(NEI)
library(ggplot2)
library(plyr)
#Retain just the Baltimore City data
NEI_Baltimore <- NEI[NEI$fips == "24510",]
#Convert type variable to a factor
NEI_Baltimore$type <- as.factor(NEI_Baltimore$type)
#Ag... |
library(lattice)
extract_chrom <- function(t, thisdata, productmz, extraction_window=0.05)
{
this_spectrum = subset(thisdata, SEC == t)
return(sum(subset(this_spectrum, MZ > productmz-(extraction_window/2) & MZ < productmz+(extraction_window/2))$INT))
}
graphme <- function(xxp,allmx){
xxp <- xxp[length(xxp):1]
... | /analysis/scripts/plotChrom.R | permissive | msproteomicstools/msproteomicstools | R | false | false | 2,920 | r | library(lattice)
extract_chrom <- function(t, thisdata, productmz, extraction_window=0.05)
{
this_spectrum = subset(thisdata, SEC == t)
return(sum(subset(this_spectrum, MZ > productmz-(extraction_window/2) & MZ < productmz+(extraction_window/2))$INT))
}
graphme <- function(xxp,allmx){
xxp <- xxp[length(xxp):1]
... |
kurtosis <-
function(x) {
x<-na.omit(x)
n<-length(x)
suma<-sum((x-mean(x))^4)/(var(x))^2
k <- n*(n+1)*suma/((n-1)*(n-2)*(n-3)) - 3*(n-1)^2/((n-2)*(n-3))
return(k)
}
| /R/kurtosis.R | no_license | cran/agricolae | R | false | false | 173 | r | kurtosis <-
function(x) {
x<-na.omit(x)
n<-length(x)
suma<-sum((x-mean(x))^4)/(var(x))^2
k <- n*(n+1)*suma/((n-1)*(n-2)*(n-3)) - 3*(n-1)^2/((n-2)*(n-3))
return(k)
}
|
library(shiny)
library(gapminder)
library(dplyr)
library(plotly)
library(ggplot2)
library()
server <- function(input, output){
rGDP <- reactive({ input$GDP })
rContinent <- reactive({ input$Continent})
output$scatterPlot <- renderPlot({
ggplot(subset(gapminder, continent == rContinent() & ... | /server.R | no_license | brianmblakely/DataProduct | R | false | false | 1,149 | r | library(shiny)
library(gapminder)
library(dplyr)
library(plotly)
library(ggplot2)
library()
server <- function(input, output){
rGDP <- reactive({ input$GDP })
rContinent <- reactive({ input$Continent})
output$scatterPlot <- renderPlot({
ggplot(subset(gapminder, continent == rContinent() & ... |
#include <AudioUnit/AudioUnit.r>
#include "FullBacanoVersion.h"
// Note that resource IDs must be spaced 2 apart for the 'STR ' name and description
#define kAudioUnitResID_FullBacano 1000
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ FullBacano~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#define RES_ID kAudioUnitRe... | /FullBacano/FullBacano/FullBacano.r | no_license | activata/FullBacano | R | false | false | 641 | r | #include <AudioUnit/AudioUnit.r>
#include "FullBacanoVersion.h"
// Note that resource IDs must be spaced 2 apart for the 'STR ' name and description
#define kAudioUnitResID_FullBacano 1000
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ FullBacano~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#define RES_ID kAudioUnitRe... |
#' Model Playground (Gadget) UI Function
#'
#' @param id, character used to specify namespace, see \code{shiny::\link[shiny]{NS}}
#'
#' @importFrom shiny tagList
#'
#' @return a \code{shiny::\link[shiny]{tag}} containing UI elements
#'
#' @export
patientGraphUI <- function(id) {
ns <- shiny::NS(id)
bs4Dash::bs4C... | /R/gadget.R | no_license | ddezel/CardioResp | R | false | false | 1,544 | r | #' Model Playground (Gadget) UI Function
#'
#' @param id, character used to specify namespace, see \code{shiny::\link[shiny]{NS}}
#'
#' @importFrom shiny tagList
#'
#' @return a \code{shiny::\link[shiny]{tag}} containing UI elements
#'
#' @export
patientGraphUI <- function(id) {
ns <- shiny::NS(id)
bs4Dash::bs4C... |
##First all data is read and then a subset is taken.
Dataset<-read.table("household_power_consumption.txt", header = TRUE, sep=";", na.strings = "?")
Dataset<-subset(Dataset, Date=="2/2/2007"|Date=="1/2/2007")
#Extra column created psting date and time together
Dataset$DateTime <-paste(Dataset$Date, Dataset$Time)
pn... | /plot2.R | no_license | FlorienM/ExData_Plotting1 | R | false | false | 556 | r | ##First all data is read and then a subset is taken.
Dataset<-read.table("household_power_consumption.txt", header = TRUE, sep=";", na.strings = "?")
Dataset<-subset(Dataset, Date=="2/2/2007"|Date=="1/2/2007")
#Extra column created psting date and time together
Dataset$DateTime <-paste(Dataset$Date, Dataset$Time)
pn... |
library(staRdom)
### Name: abs_fit_slope
### Title: Fit absorbance data to exponential curve. 'drm' is used for the
### fitting process.
### Aliases: abs_fit_slope
### ** Examples
data(abs_data)
abs_fit_slope(abs_data$wavelength,abs_data$sample1,lim=c(350,400),l_ref=350)
| /data/genthat_extracted_code/staRdom/examples/abs_fit_slope.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 281 | r | library(staRdom)
### Name: abs_fit_slope
### Title: Fit absorbance data to exponential curve. 'drm' is used for the
### fitting process.
### Aliases: abs_fit_slope
### ** Examples
data(abs_data)
abs_fit_slope(abs_data$wavelength,abs_data$sample1,lim=c(350,400),l_ref=350)
|
makeCacheMatrix <- function(x = matrix()) {
invrs <- NULL
setorig <- function(y) {
x <<- y
invrs <<- NULL
}
getorig <- function() x
setinversevalue <- function(inverse) invrs <<- inverse
getinversevalue <- function() invrs
list(set = setorig,
get = getorig,
setinverse = ... | /cachematrix.R | no_license | manjuvegesna/ProgrammingAssignment2 | R | false | false | 649 | r |
makeCacheMatrix <- function(x = matrix()) {
invrs <- NULL
setorig <- function(y) {
x <<- y
invrs <<- NULL
}
getorig <- function() x
setinversevalue <- function(inverse) invrs <<- inverse
getinversevalue <- function() invrs
list(set = setorig,
get = getorig,
setinverse = ... |
\name{Zimmerman}
\alias{Zimmerman}
\docType{data}
\title{Stand Your Ground Simpson's Paradox }
\description{
Data from 220 cases in Florida where a "Stand your ground" defense was used.
}
\format{
A data frame with 220 observations on the following 5 variables.
\describe{
\item{\code{Convicted}}{Was the defenda... | /man/Zimmerman.Rd | permissive | tessington/qsci381 | R | false | false | 1,223 | rd | \name{Zimmerman}
\alias{Zimmerman}
\docType{data}
\title{Stand Your Ground Simpson's Paradox }
\description{
Data from 220 cases in Florida where a "Stand your ground" defense was used.
}
\format{
A data frame with 220 observations on the following 5 variables.
\describe{
\item{\code{Convicted}}{Was the defenda... |
#' Estimates principal component functions by computing eigenfunctions of the covariance function
#'
#' Estimates principal component functions by computing eigenfunctions of the covariance function
#'
#' @param dat functional data set that can be passed to \code{ssfcov2::estimate_cov_function()}. See documentation f... | /R/fpca_ss.R | no_license | dan410/SimStudy_eigenfunction_estimation | R | false | false | 955 | r | #' Estimates principal component functions by computing eigenfunctions of the covariance function
#'
#' Estimates principal component functions by computing eigenfunctions of the covariance function
#'
#' @param dat functional data set that can be passed to \code{ssfcov2::estimate_cov_function()}. See documentation f... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/extract.R
\name{extract_1d}
\alias{extract_1d}
\title{Extract 1d Values}
\usage{
extract_1d(core_table = NULL, input = NULL, data_location = NULL)
}
\arguments{
\item{core_table}{the core table from make_core}
\item{input}{the HIC code for t... | /man/extract_1d.Rd | no_license | CC-HIC/inspectEHR | R | false | true | 621 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/extract.R
\name{extract_1d}
\alias{extract_1d}
\title{Extract 1d Values}
\usage{
extract_1d(core_table = NULL, input = NULL, data_location = NULL)
}
\arguments{
\item{core_table}{the core table from make_core}
\item{input}{the HIC code for t... |
main <- function() {
library(sqldf)
data <- read.csv.sql("household_power_consumption.txt", sql = "select * from file where Date = '1/2/2007' OR Date = '2/2/2007'", eol = "\n", header = TRUE, sep = ";")dat$DateTime <- strptime(paste(dat$Date, dat$Time), "%d/%m/%Y %H:%M")
data$DateTime <- strptime(paste(dat... | /plot2.R | no_license | pnwhitney/ExData_Plotting1 | R | false | false | 525 | r | main <- function() {
library(sqldf)
data <- read.csv.sql("household_power_consumption.txt", sql = "select * from file where Date = '1/2/2007' OR Date = '2/2/2007'", eol = "\n", header = TRUE, sep = ";")dat$DateTime <- strptime(paste(dat$Date, dat$Time), "%d/%m/%Y %H:%M")
data$DateTime <- strptime(paste(dat... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ggplot_util.R
\name{geom_txt}
\alias{geom_txt}
\title{geom_txt}
\usage{
geom_txt(..., family = theme_get()$text$family, size = 3,
colour = "#2b2b2b")
}
\arguments{
\item{...}{Passed to \code{geom_text}.}
\item{family}{Font family. Default... | /man/geom_txt.Rd | no_license | arbelt/azwmisc | R | false | true | 510 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ggplot_util.R
\name{geom_txt}
\alias{geom_txt}
\title{geom_txt}
\usage{
geom_txt(..., family = theme_get()$text$family, size = 3,
colour = "#2b2b2b")
}
\arguments{
\item{...}{Passed to \code{geom_text}.}
\item{family}{Font family. Default... |
library(testthat)
library(BrokenAdaptiveRidge)
test_check("BrokenAdaptiveRidge")
| /tests/testthat.R | permissive | yuxitian/BrokenAdaptiveRidge | R | false | false | 82 | r | library(testthat)
library(BrokenAdaptiveRidge)
test_check("BrokenAdaptiveRidge")
|
library(shiny)
CohortEffect <- function(x1,
x2,
min.meaningful.effect) {
dat <- data.frame(y=c(x1,x2),
d2=c(rep(0, length(x1)), rep(1, length(x2))))
res <- lm(y ~ d2, data=dat)
coefs <- summary(res)$coefficients
effect.mean <- coefs[2,1]
... | /demo/ab/server.R | no_license | shaptonstahl/abtest | R | false | false | 6,607 | r | library(shiny)
CohortEffect <- function(x1,
x2,
min.meaningful.effect) {
dat <- data.frame(y=c(x1,x2),
d2=c(rep(0, length(x1)), rep(1, length(x2))))
res <- lm(y ~ d2, data=dat)
coefs <- summary(res)$coefficients
effect.mean <- coefs[2,1]
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/geom.mean.R
\name{geom.mean}
\alias{geom.mean}
\title{Geometric Mean}
\usage{
geom.mean(x)
}
\arguments{
\item{x}{a numeric vector for which geometric mean computations shall be performed.}
}
\description{
This function computes the geometric... | /man/geom.mean.Rd | no_license | AcaDemIQ/myTAI | R | false | true | 431 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/geom.mean.R
\name{geom.mean}
\alias{geom.mean}
\title{Geometric Mean}
\usage{
geom.mean(x)
}
\arguments{
\item{x}{a numeric vector for which geometric mean computations shall be performed.}
}
\description{
This function computes the geometric... |
# #Upload to Shiny IO
# install.packages('rsconnect')
# library(rsconnect)
#install.packages(c('shiny','DT','ggplot2','purrr','dplyr','corrplot','plotly','randomForest'))
#
# rsconnect::setAccountInfo(name='chrisedstrom', token='88D536E091400263E74E70661483E0F1', secret='OYmlIwBg/jZdy9htFnQf8Kgex0crEwWkYFQKLOf4')... | /App5.R | no_license | ChrisEdstrom/Shiny | R | false | false | 16,027 | r | # #Upload to Shiny IO
# install.packages('rsconnect')
# library(rsconnect)
#install.packages(c('shiny','DT','ggplot2','purrr','dplyr','corrplot','plotly','randomForest'))
#
# rsconnect::setAccountInfo(name='chrisedstrom', token='88D536E091400263E74E70661483E0F1', secret='OYmlIwBg/jZdy9htFnQf8Kgex0crEwWkYFQKLOf4')... |
#' Classify a review as good or bad
#'
#' @param x Text to be classified, ideally a one-sentence product review.
#' @param random_forest A model created with the randomForest package.
#' @param vectoriser A vectoriser constructed with the text2vec package.
#' @param tfidf A tfidf object constructed with the text2vec pa... | /R/sentiment.R | permissive | mdneuzerling/ReviewSentiment | R | false | false | 641 | r | #' Classify a review as good or bad
#'
#' @param x Text to be classified, ideally a one-sentence product review.
#' @param random_forest A model created with the randomForest package.
#' @param vectoriser A vectoriser constructed with the text2vec package.
#' @param tfidf A tfidf object constructed with the text2vec pa... |
#'
Predict1Word.UsingNgram__Generator__ <- function(DFMs) {
freqNgrams <- lapply(1:length(DFMs), function(N) {
freq <- colSums(DFMs[[N]]) %>%
as.data.table(keep.rownames = "Ngram") %>%
.[, `:=`(c("Ngram", paste0("Word", (N-1):0)),
strsplit(Ngram, "_")... | /Week3Tasks.R | no_license | lchiaying/Coursera-DataScienceSpecialization-Capstone | R | false | false | 5,444 | r |
#'
Predict1Word.UsingNgram__Generator__ <- function(DFMs) {
freqNgrams <- lapply(1:length(DFMs), function(N) {
freq <- colSums(DFMs[[N]]) %>%
as.data.table(keep.rownames = "Ngram") %>%
.[, `:=`(c("Ngram", paste0("Word", (N-1):0)),
strsplit(Ngram, "_")... |
## hpc = Household Power Consumption
library(data.table)
library(dplyr)
## Removes all pre-existing variables.
rm(list = ls())
## Set working directory to preferred folder on Desktop
setwd('C:/Users/mhgandhi/Desktop/Data Science Specialization/Course 4 - Exploratory Data Analysis/
Week 1/Course... | /Plot 4.R | no_license | montoohg/ExData_Plotting1 | R | false | false | 2,539 | r | ## hpc = Household Power Consumption
library(data.table)
library(dplyr)
## Removes all pre-existing variables.
rm(list = ls())
## Set working directory to preferred folder on Desktop
setwd('C:/Users/mhgandhi/Desktop/Data Science Specialization/Course 4 - Exploratory Data Analysis/
Week 1/Course... |
#!/usr/local/bin/R
ApeShape_withprint <- function(infile, inTree){
args <- commandArgs(trailingOnly=TRUE)
library(phangorn)
library(ape)
tree <- read.tree(file= args[2])
seq <- read.FASTA(file= args[1])
phyDat <- phyDat(seq,type="DNA")
treePML <- pml(tree,phyDat)
anc <- ancestral.pml(treePML)
baseIndex <- which.... | /R/ApeShape_withprint.R | permissive | jbeacher6/ApeShape | R | false | false | 573 | r | #!/usr/local/bin/R
ApeShape_withprint <- function(infile, inTree){
args <- commandArgs(trailingOnly=TRUE)
library(phangorn)
library(ape)
tree <- read.tree(file= args[2])
seq <- read.FASTA(file= args[1])
phyDat <- phyDat(seq,type="DNA")
treePML <- pml(tree,phyDat)
anc <- ancestral.pml(treePML)
baseIndex <- which.... |
library("stringr")
library("purrr")
| /libraries.R | no_license | czeildi/r-dojo | R | false | false | 36 | r | library("stringr")
library("purrr")
|
#' Is an object an expression?
#'
#' @description
#' In rlang, an _expression_ is the return type of [parse_expr()], the
#' set of objects that can be obtained from parsing R code. Under this
#' definition expressions include numbers, strings, `NULL`, symbols,
#' and function calls. These objects can be classified as:
... | /R/expr.R | permissive | seankross/rlang | R | false | false | 11,290 | r | #' Is an object an expression?
#'
#' @description
#' In rlang, an _expression_ is the return type of [parse_expr()], the
#' set of objects that can be obtained from parsing R code. Under this
#' definition expressions include numbers, strings, `NULL`, symbols,
#' and function calls. These objects can be classified as:
... |
library(markovchain)
library(expm)
lambda<- 1
mu <- 2
rho<- 3
gamma<- 4
estadosCarga<-c(0,10,20,30,40,50,60,70,80,90,100)
estadosBooleano<-c(0:1)
estados=as.vector(outer(estadosBooleano, estadosCarga, paste, sep=","))
estados
matrizQ<-matrix(0,nrow=length(estados),ncol=length(estados))
colnames(matrizQ)=estados
rowna... | /Archivo R.R | no_license | jc-corrales/SMS-Sachsen | R | false | false | 1,127 | r | library(markovchain)
library(expm)
lambda<- 1
mu <- 2
rho<- 3
gamma<- 4
estadosCarga<-c(0,10,20,30,40,50,60,70,80,90,100)
estadosBooleano<-c(0:1)
estados=as.vector(outer(estadosBooleano, estadosCarga, paste, sep=","))
estados
matrizQ<-matrix(0,nrow=length(estados),ncol=length(estados))
colnames(matrizQ)=estados
rowna... |
# read and clean 16S ------------------------------------------------------
# setwd("~/Desktop/R/CMAIKI_clean_and_query/bacterial_16S/")
# clean 16S pipeline outputs for R analyses
clean_16S_tables <- function(abundance_file = NULL,
taxonomy_file = NULL,
met... | /src/clean_and_query_16S.R | no_license | soswift/waimea_marine | R | false | false | 8,059 | r |
# read and clean 16S ------------------------------------------------------
# setwd("~/Desktop/R/CMAIKI_clean_and_query/bacterial_16S/")
# clean 16S pipeline outputs for R analyses
clean_16S_tables <- function(abundance_file = NULL,
taxonomy_file = NULL,
met... |
library(ensembleBMA)
### Name: ymdhTOjul
### Title: Convert to Julian dates.
### Aliases: ymdhTOjul
### Keywords: chron
### ** Examples
data(ensBMAtest)
julianVdates <- ymdhTOjul(ensBMAtest$vdate)
all.equal( julTOymdh(julianVdates), as.character(ensBMAtest$vdate))
all.equal( ymdhTOjul(ensBMAtest$idate), j... | /data/genthat_extracted_code/ensembleBMA/examples/ymdhTOjul.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 338 | r | library(ensembleBMA)
### Name: ymdhTOjul
### Title: Convert to Julian dates.
### Aliases: ymdhTOjul
### Keywords: chron
### ** Examples
data(ensBMAtest)
julianVdates <- ymdhTOjul(ensBMAtest$vdate)
all.equal( julTOymdh(julianVdates), as.character(ensBMAtest$vdate))
all.equal( ymdhTOjul(ensBMAtest$idate), j... |
#Ex1.1, Page 4
library(lattice)
data<-c(6.1,12.6,34.7,1.6,18.8,2.2,3.0,2.2,5.6,3.8,2.2,3.1,1.3,1.1,14.1,4.0,21.0,6.1,1.3,20.4,7.5,3.9,10.1,8.1,19.5,5.2,12.0,15.8,10.4,5.2,6.4,10.8,83.1,3.6,6.2,6.3,16.3,12.7,1.3,0.8,8.8,5.1,3.7,26.3,6.0,48.0,8.2,11.7,7.2,3.9,15.3,16.6,8.8,12.0,4.7,14.7,6.4,17.0,2.5,16.2)
stem(d... | /Probability_And_Statistics_For_Engineering_And_The_Sciences_by_Jay_L_Devore/CH1/EX1.1/Ex1_1.R | permissive | FOSSEE/R_TBC_Uploads | R | false | false | 462 | r | #Ex1.1, Page 4
library(lattice)
data<-c(6.1,12.6,34.7,1.6,18.8,2.2,3.0,2.2,5.6,3.8,2.2,3.1,1.3,1.1,14.1,4.0,21.0,6.1,1.3,20.4,7.5,3.9,10.1,8.1,19.5,5.2,12.0,15.8,10.4,5.2,6.4,10.8,83.1,3.6,6.2,6.3,16.3,12.7,1.3,0.8,8.8,5.1,3.7,26.3,6.0,48.0,8.2,11.7,7.2,3.9,15.3,16.6,8.8,12.0,4.7,14.7,6.4,17.0,2.5,16.2)
stem(d... |
setwd("C:\\users\\zhuangmg\\coursera\\exploratory data analysis\\project 1")
list.files()
data<-read.csv("./household_power_consumption.txt", sep=';',na.strings="?", nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"')
data2<-na.omit(data)
library(data.table)
fulldata<-data.table(data2)
## Su... | /plot3.R | no_license | mandyzzz/ExData_Plotting1 | R | false | false | 1,165 | r | setwd("C:\\users\\zhuangmg\\coursera\\exploratory data analysis\\project 1")
list.files()
data<-read.csv("./household_power_consumption.txt", sep=';',na.strings="?", nrows=2075259, check.names=F, stringsAsFactors=F, comment.char="", quote='\"')
data2<-na.omit(data)
library(data.table)
fulldata<-data.table(data2)
## Su... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/termsInfo.R
\name{tidy_smooth2d}
\alias{tidy_smooth2d}
\title{Extract 2d smooth objects in tidy format.}
\usage{
tidy_smooth2d(x, keep = c("x", "y", "fit", "se", "xlab", "ylab", "main"),
ci = FALSE, ...)
}
\arguments{
\item{x}{ a fitted \co... | /man/tidy_smooth2d.Rd | no_license | adibender/pam | R | false | true | 668 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/termsInfo.R
\name{tidy_smooth2d}
\alias{tidy_smooth2d}
\title{Extract 2d smooth objects in tidy format.}
\usage{
tidy_smooth2d(x, keep = c("x", "y", "fit", "se", "xlab", "ylab", "main"),
ci = FALSE, ...)
}
\arguments{
\item{x}{ a fitted \co... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/util-export.R
\name{writeDatabaseData}
\alias{writeDatabaseData}
\title{Write feature data frame to a database}
\usage{
writeDatabaseData(data, name = NULL, label = NULL, conn, overwrite = TRUE,
runConfig)
}
\arguments{
\item{data}{The feat... | /man/writeDatabaseData.Rd | permissive | ahmeduncc/visdom-1 | R | false | true | 991 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/util-export.R
\name{writeDatabaseData}
\alias{writeDatabaseData}
\title{Write feature data frame to a database}
\usage{
writeDatabaseData(data, name = NULL, label = NULL, conn, overwrite = TRUE,
runConfig)
}
\arguments{
\item{data}{The feat... |
> fa.parallel(mydata,fa="pc")
Parallel analysis suggests that the number of factors = NA and the number of components = 2
> scree(mydata)
2 componenten
> VSS(mydata,rotate="promax", fm="pc")
Very Simple Structure
Call: vss(x = x, n = n, rotate = rotate, diagonal = diagonal, fm = fm,
n.obs = n.obs, plo... | /Masterarbeit/R-Berechnungen/Hauptkomponentenanylyse_aktuell.R | no_license | karpyuk/TeX | R | false | false | 9,640 | r | > fa.parallel(mydata,fa="pc")
Parallel analysis suggests that the number of factors = NA and the number of components = 2
> scree(mydata)
2 componenten
> VSS(mydata,rotate="promax", fm="pc")
Very Simple Structure
Call: vss(x = x, n = n, rotate = rotate, diagonal = diagonal, fm = fm,
n.obs = n.obs, plo... |
bayesLogNormalTest <- function(A_data,
B_data,
priors,
n_samples = 1e5) {
###
## Error Checking
###
if((
any(
A_data <= 0,
B_data <= 0
)
)) {
stop("Data input is incorrect. The support of... | /R/dist-lognormal.R | no_license | bryant1410/bayesAB | R | false | false | 1,556 | r | bayesLogNormalTest <- function(A_data,
B_data,
priors,
n_samples = 1e5) {
###
## Error Checking
###
if((
any(
A_data <= 0,
B_data <= 0
)
)) {
stop("Data input is incorrect. The support of... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/extract.stringCode.R
\name{from.TreeCode}
\alias{from.TreeCode}
\title{from.TreeCode}
\usage{
from.TreeCode(x)
}
\description{
from.TreeCode
}
| /modules/data.land/man/from.TreeCode.Rd | permissive | PecanProject/pecan | R | false | true | 221 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/extract.stringCode.R
\name{from.TreeCode}
\alias{from.TreeCode}
\title{from.TreeCode}
\usage{
from.TreeCode(x)
}
\description{
from.TreeCode
}
|
load("E:\\Research\\NRIIDI revisions\\Cox\\NRIWBUsingCox400_Alternative.rda")
load("E:\\Research\\NRIIDI revisions\\Cox\\NRIWBUsingFine400_Alternative.rda")
load("E:\\Research\\NRIIDI revisions\\Cox\\NRIWBUsingCox200_Alternative.rda")
load("E:\\Research\\NRIIDI revisions\\Cox\\NRIWBUsingFine200_Alternative.rda")
load("... | /Simulation/Cox/result_viewer_alternative.R | permissive | WangandYu/NRIandIDI | R | false | false | 14,098 | r | load("E:\\Research\\NRIIDI revisions\\Cox\\NRIWBUsingCox400_Alternative.rda")
load("E:\\Research\\NRIIDI revisions\\Cox\\NRIWBUsingFine400_Alternative.rda")
load("E:\\Research\\NRIIDI revisions\\Cox\\NRIWBUsingCox200_Alternative.rda")
load("E:\\Research\\NRIIDI revisions\\Cox\\NRIWBUsingFine200_Alternative.rda")
load("... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{covCMB_internal2}
\alias{covCMB_internal2}
\title{covCMB_internal2}
\usage{
covCMB_internal2(cmbdf, nbin)
}
| /man/covCMB_internal2.Rd | permissive | mingltu/rcosmo | R | false | true | 214 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{covCMB_internal2}
\alias{covCMB_internal2}
\title{covCMB_internal2}
\usage{
covCMB_internal2(cmbdf, nbin)
}
|
% Generated by roxygen2 (4.0.2): do not edit by hand
\name{print.cumulative_syllable_freq}
\alias{print.cumulative_syllable_freq}
\title{Prints a cumulative_syllable_freqObject}
\usage{
\method{print}{cumulative_syllable_freq}(x, ...)
}
\arguments{
\item{x}{The cumulative_syllable_freqobject.}
\item{\ldots}{ignored}
}... | /man/print.cumulative_syllable_freq.Rd | no_license | joffrevillanueva/qdap | R | false | false | 380 | rd | % Generated by roxygen2 (4.0.2): do not edit by hand
\name{print.cumulative_syllable_freq}
\alias{print.cumulative_syllable_freq}
\title{Prints a cumulative_syllable_freqObject}
\usage{
\method{print}{cumulative_syllable_freq}(x, ...)
}
\arguments{
\item{x}{The cumulative_syllable_freqobject.}
\item{\ldots}{ignored}
}... |
# ----------------------------------------------------
# Initial data hacking for Ch 5: Primary Election Outcomes
# This file begins: May 13, 2020
# ----------------------------------------------------
library("here")
library("magrittr")
library("tidyverse")
library("broom")
# library("tidybayes")
library("boxr");... | /code/05-voting/51_voting-eda.R | no_license | mikedecr/dissertation | R | false | false | 15,469 | r | # ----------------------------------------------------
# Initial data hacking for Ch 5: Primary Election Outcomes
# This file begins: May 13, 2020
# ----------------------------------------------------
library("here")
library("magrittr")
library("tidyverse")
library("broom")
# library("tidybayes")
library("boxr");... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/models.R
\name{shim}
\alias{shim}
\title{Fit Strong Heredity Interaction Model}
\usage{
shim(x, y, main.effect.names, interaction.names, family = c("gaussian",
"binomial", "poisson"), weights, lambda.factor = ifelse(nobs < nvars, 0.01,
1e... | /man/shim.Rd | no_license | friendlywlb/shim | R | false | true | 9,007 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/models.R
\name{shim}
\alias{shim}
\title{Fit Strong Heredity Interaction Model}
\usage{
shim(x, y, main.effect.names, interaction.names, family = c("gaussian",
"binomial", "poisson"), weights, lambda.factor = ifelse(nobs < nvars, 0.01,
1e... |
#' Check correct input DNA sequence
#'
#' @param secuencia character: coding dna, must be in frame
#'
#' @return throws an error if the sequence contains invalid characters or is not a
#' multiple of 3
#' @export
#'
#' @examples
#' validate_sequence(test_seq)
validate_sequence <- function(secuencia) {
secuencia <- s... | /R/utilities.R | permissive | santiago1234/iCodon | R | false | false | 4,863 | r | #' Check correct input DNA sequence
#'
#' @param secuencia character: coding dna, must be in frame
#'
#' @return throws an error if the sequence contains invalid characters or is not a
#' multiple of 3
#' @export
#'
#' @examples
#' validate_sequence(test_seq)
validate_sequence <- function(secuencia) {
secuencia <- s... |
\name{portfolio_getSettings}
\alias{portfolio_getSettings}
\title{Get Portfolio Settings}
\usage{portfolio_getSettings(portfolio)
}
\arguments{
\item{portfolio}{Portfolio object created using \link[=portfolio_create]{portfolio_create( )} function}
}
\value{List with portfolio settings.}
\description{Method r... | /man/portfolio_getSettings.Rd | no_license | IanMadlenya/PortfolioEffectHFT | R | false | false | 1,113 | rd | \name{portfolio_getSettings}
\alias{portfolio_getSettings}
\title{Get Portfolio Settings}
\usage{portfolio_getSettings(portfolio)
}
\arguments{
\item{portfolio}{Portfolio object created using \link[=portfolio_create]{portfolio_create( )} function}
}
\value{List with portfolio settings.}
\description{Method r... |
#-----------------------------------
# Objeto da Classe Tree
#-----------------------------------
# --- Facilitando a importacao dos dados ---
diretorio ="E:\\Academico\\Mestrado\\Tese\\ws\\trans\\zf2"
# inp <- file_path_sans_ext(dir(paste0(diretorio,"\\laz\\"),pattern='.laz')) #colocar arquivos na pasta laz
#... | /objetoTree.R | no_license | gustavohom/FusionEmergent | R | false | false | 759 | r | #-----------------------------------
# Objeto da Classe Tree
#-----------------------------------
# --- Facilitando a importacao dos dados ---
diretorio ="E:\\Academico\\Mestrado\\Tese\\ws\\trans\\zf2"
# inp <- file_path_sans_ext(dir(paste0(diretorio,"\\laz\\"),pattern='.laz')) #colocar arquivos na pasta laz
#... |
#!/usr/bin/env Rscript
suppressPackageStartupMessages(library(tidyverse))
suppressPackageStartupMessages(library(synapser))
suppressPackageStartupMessages(library(assertr))
suppressPackageStartupMessages(library(agoradataprocessing))
suppressPackageStartupMessages(library("optparse"))
option_list <- list(
make_opti... | /exec/process.R | permissive | mfazza/agoradataprocessing | R | false | false | 4,462 | r | #!/usr/bin/env Rscript
suppressPackageStartupMessages(library(tidyverse))
suppressPackageStartupMessages(library(synapser))
suppressPackageStartupMessages(library(assertr))
suppressPackageStartupMessages(library(agoradataprocessing))
suppressPackageStartupMessages(library("optparse"))
option_list <- list(
make_opti... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/IsBinary.R
\name{is.binary}
\alias{is.binary}
\title{Calculate cross validation penalty}
\usage{
is.binary(x)
}
\arguments{
\item{x}{a numeric vector}
}
\description{
\code{is.binary} returns TRUE if a variable is binary, and FALSE ot... | /man/is.binary.Rd | no_license | EricZhao636/Information | R | false | false | 331 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/IsBinary.R
\name{is.binary}
\alias{is.binary}
\title{Calculate cross validation penalty}
\usage{
is.binary(x)
}
\arguments{
\item{x}{a numeric vector}
}
\description{
\code{is.binary} returns TRUE if a variable is binary, and FALSE ot... |
# con questo processo si considera pari a zero i values dei battelli non inviati, quindi si esegue l'espansione ricalcolando le pr_i che inizialmente sono Inf per i sent=0 & id_battello>0
# calcola pr_i ####
setkey(flotta, id_strato)
flotta_temp=flotta[.( as.numeric(input_strato_imp_m()) )][,list(id_strato,lft,id_bat... | /source/refresh_pr_i_imp_m.R | no_license | micheledemeo/datacontrol | R | false | false | 2,288 | r | # con questo processo si considera pari a zero i values dei battelli non inviati, quindi si esegue l'espansione ricalcolando le pr_i che inizialmente sono Inf per i sent=0 & id_battello>0
# calcola pr_i ####
setkey(flotta, id_strato)
flotta_temp=flotta[.( as.numeric(input_strato_imp_m()) )][,list(id_strato,lft,id_bat... |
library(PReMiuM)
library(tidyverse)
# library(parallel)
# require(doMC)
# require(foreach)
setwd("/work/04734/dhbrand/stampede2/GitHub/EnviroTyping/data/interim/G2F_Hybrid/hyb_by_month_preds/full_long")
df <- read_rds("../../hybrid_by_month_calibrated_weather.rds")
#subset <- df[sample(1:nrow(df),.1*dim(df)[1]),]
se... | /sandbox/hyb_by_month_preds/full_long.R | no_license | TACC/EnviroTyping | R | false | false | 4,563 | r | library(PReMiuM)
library(tidyverse)
# library(parallel)
# require(doMC)
# require(foreach)
setwd("/work/04734/dhbrand/stampede2/GitHub/EnviroTyping/data/interim/G2F_Hybrid/hyb_by_month_preds/full_long")
df <- read_rds("../../hybrid_by_month_calibrated_weather.rds")
#subset <- df[sample(1:nrow(df),.1*dim(df)[1]),]
se... |
# -----------------------------------------
#Midwestern agriculture synthesis Shiny app
# -----------------------------------------
# Managing Soil Carbon - SNAPP Working Group
library("shiny") # for making Shiny app
library("dplyr") # for sorting and summarizing data
library("readxl") # for importing d... | /www/app.R | no_license | kanedan29/Midwest-Agriculture-Synthesis | R | false | false | 10,630 | r | # -----------------------------------------
#Midwestern agriculture synthesis Shiny app
# -----------------------------------------
# Managing Soil Carbon - SNAPP Working Group
library("shiny") # for making Shiny app
library("dplyr") # for sorting and summarizing data
library("readxl") # for importing d... |
#Set Working Directory
#Windows @ UA
setwd("C:/Users/avanderlaar/Dropbox/R/Distance/")
#add these libraries
library(unmarked)
library(AICcmodavg)
#Read in the bird detection information
dists<-read.csv('Sora13.csv', header=TRUE)
#reading in the habitat information
soracov<-read.csv('Veg13_min.csv', header=TRUE )
... | /old_awful_code/Distance.R | no_license | aurielfournier/my_unmarked_code | R | false | false | 15,582 | r | #Set Working Directory
#Windows @ UA
setwd("C:/Users/avanderlaar/Dropbox/R/Distance/")
#add these libraries
library(unmarked)
library(AICcmodavg)
#Read in the bird detection information
dists<-read.csv('Sora13.csv', header=TRUE)
#reading in the habitat information
soracov<-read.csv('Veg13_min.csv', header=TRUE )
... |
library(readxl)
schema<-read_xlsx(file.choose()) #
data1<-read_xlsx(file.choose()) #
#data2<-read.csv(file.choose(),header = T,stringsAsFactors = F) #
col.name<-schema[schema$TableName=='Name',"ColumnName"]# extract colummn name of schema of a particular table
num.col.name<-nrow(col.name) # number of column of ta... | /BagOfWords/field-mapping_word_mapping.R | no_license | SrijaGupta/CapstoneProject-IDS507 | R | false | false | 1,215 | r | library(readxl)
schema<-read_xlsx(file.choose()) #
data1<-read_xlsx(file.choose()) #
#data2<-read.csv(file.choose(),header = T,stringsAsFactors = F) #
col.name<-schema[schema$TableName=='Name',"ColumnName"]# extract colummn name of schema of a particular table
num.col.name<-nrow(col.name) # number of column of ta... |
#' Generate a mixed design from existing data
#'
#' \code{sim_mixed_df()} produces a data table with the same distributions of
#' by-subject and by-item random intercepts as an existing data table.
#'
#' @param data the existing tbl
#' @param sub_n the number of subjects to simulate (if NULL, returns data for the same... | /R/sim_mixed_df.R | permissive | debruine/faux | R | false | false | 1,525 | r | #' Generate a mixed design from existing data
#'
#' \code{sim_mixed_df()} produces a data table with the same distributions of
#' by-subject and by-item random intercepts as an existing data table.
#'
#' @param data the existing tbl
#' @param sub_n the number of subjects to simulate (if NULL, returns data for the same... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/phaseImpute.R
\name{prePhasingByShapeit}
\alias{prePhasingByShapeit}
\title{Prephasing genotypes using SHAPEIT}
\usage{
prePhasingByShapeit(shapeit, chrs, dataDIR, prefix4plinkEachChr, impRefDIR,
phaseDIR, nThread, effectiveSize, nCore)
}
\... | /man/prePhasingByShapeit.Rd | no_license | Junfang/Gimpute | R | false | true | 1,397 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/phaseImpute.R
\name{prePhasingByShapeit}
\alias{prePhasingByShapeit}
\title{Prephasing genotypes using SHAPEIT}
\usage{
prePhasingByShapeit(shapeit, chrs, dataDIR, prefix4plinkEachChr, impRefDIR,
phaseDIR, nThread, effectiveSize, nCore)
}
\... |
#[export]
kurt.test2 <- function(x, y) {
n1 <- length(x)
n2 <- length(y)
vars1 <- 24 * n1 * (n1 -1 )^2 / ( (n1 - 3) * (n1 - 2) * (n1 + 3) * (n1 + 5) )
vars2 <- 24 * n2 * (n2 - 1)^2 / ( (n2 - 3) * (n2 - 2) * (n2 + 3) * (n2 + 5) )
stat <- ( Rfast::kurt(x) - Rfast::kurt(y) ) / sqrt( vars1 + vars2 )
pva... | /fuzzedpackages/Rfast/R/kurt.test2.R | no_license | akhikolla/testpackages | R | false | false | 442 | r | #[export]
kurt.test2 <- function(x, y) {
n1 <- length(x)
n2 <- length(y)
vars1 <- 24 * n1 * (n1 -1 )^2 / ( (n1 - 3) * (n1 - 2) * (n1 + 3) * (n1 + 5) )
vars2 <- 24 * n2 * (n2 - 1)^2 / ( (n2 - 3) * (n2 - 2) * (n2 + 3) * (n2 + 5) )
stat <- ( Rfast::kurt(x) - Rfast::kurt(y) ) / sqrt( vars1 + vars2 )
pva... |
#' VS-Lite model of tree ring width growth.
#'
#' \code{VSLite} simulates tree ring width growth.
#'
#' R port of VS-Lite Model of Tree Ring Width by Suz TOlwinski-Ward, 2015. For more references,
#' see xxxxyyyyyzzzz.
#'
#' @param syear Start year of simulation.
#' @param eyear End year of simulation.
#' @param phi... | /R/VSLite.R | no_license | fzhu2e/VSLiteR | R | false | false | 5,671 | r | #' VS-Lite model of tree ring width growth.
#'
#' \code{VSLite} simulates tree ring width growth.
#'
#' R port of VS-Lite Model of Tree Ring Width by Suz TOlwinski-Ward, 2015. For more references,
#' see xxxxyyyyyzzzz.
#'
#' @param syear Start year of simulation.
#' @param eyear End year of simulation.
#' @param phi... |
library(tidyverse)
library(dplyr)
library(ggplot2)
library(grid)
library(cowplot)
library(readxl)
Bentho <- read_xlsx(here::here("Analysis", "Data", "2018 Tiles Allison's Computer.xlsx"),
sheet = "2017 and 2018")
Snails <- read_xlsx(here::here("Analysis", "Data", "2018 Tiles Allison's Computer.xl... | /Analysis/R/snail BACI.R | no_license | Cedar-Mac/Thesis | R | false | false | 4,338 | r | library(tidyverse)
library(dplyr)
library(ggplot2)
library(grid)
library(cowplot)
library(readxl)
Bentho <- read_xlsx(here::here("Analysis", "Data", "2018 Tiles Allison's Computer.xlsx"),
sheet = "2017 and 2018")
Snails <- read_xlsx(here::here("Analysis", "Data", "2018 Tiles Allison's Computer.xl... |
# Building a Prod-Ready, Robust Shiny Application.
#
# Each step is optional.
#
# 1 - On init
#
## 1.1 - Fill the descripion & set options
##
## Add information about the package that will contain your app
golem::fill_desc(
pkg_name = "OB1.metadata", # The Name of the package containing the App
pkg_title = "... | /dev/01_start.R | permissive | pole-national-donnees-biodiversite/OB1.metadata | R | false | false | 1,869 | r | # Building a Prod-Ready, Robust Shiny Application.
#
# Each step is optional.
#
# 1 - On init
#
## 1.1 - Fill the descripion & set options
##
## Add information about the package that will contain your app
golem::fill_desc(
pkg_name = "OB1.metadata", # The Name of the package containing the App
pkg_title = "... |
load('Rdata/lmer-perROI-out-invage.Rdata')
ageeff <- read.csv('txt/ageeffAgeXphys-invage.csv')
#best.lm <- roirois.lm[order(ageeff$ageXphysio.tval)[1:300]]
#best.lm.order <- order(ageeff$ageXphysio.tval)[1:300]
# only use significant ROIs
ageeff.sigidx <- which(abs(ageeff$ageXphysio.tval)>2.58)
# grav tvalues at sigin... | /truncateLM.R | no_license | WillForan/physioCompare | R | false | false | 862 | r | load('Rdata/lmer-perROI-out-invage.Rdata')
ageeff <- read.csv('txt/ageeffAgeXphys-invage.csv')
#best.lm <- roirois.lm[order(ageeff$ageXphysio.tval)[1:300]]
#best.lm.order <- order(ageeff$ageXphysio.tval)[1:300]
# only use significant ROIs
ageeff.sigidx <- which(abs(ageeff$ageXphysio.tval)>2.58)
# grav tvalues at sigin... |
#QCA Plots
#btw, small modifications of this could replace the current scripts for returning the final data set
#need to change the configuration.table file though (and the regression analysis)
source("sim.ltQCA.R")
library(QCA)
library(foreach)
#create a data set with varying distributions, and varying number of var... | /qcaeval.old/final_data_set (Ben Gibson's conflicted copy 2015-05-05).R | no_license | cbengibson/QCArevision2 | R | false | false | 1,332 | r | #QCA Plots
#btw, small modifications of this could replace the current scripts for returning the final data set
#need to change the configuration.table file though (and the regression analysis)
source("sim.ltQCA.R")
library(QCA)
library(foreach)
#create a data set with varying distributions, and varying number of var... |
#This script integrates the graphs for plot 2 and plot 3, among with the plots
#for Voltage and Gobal_reactive_power in a single image.
#Data preparation
#Read the header
firstLine <- read.table("./household_power_consumption.txt", header = TRUE,
sep = ";", na.strings = "?", nrows = 1)
#Read th... | /plot4.R | no_license | sotmihos/ExData_Plotting1 | R | false | false | 2,136 | r | #This script integrates the graphs for plot 2 and plot 3, among with the plots
#for Voltage and Gobal_reactive_power in a single image.
#Data preparation
#Read the header
firstLine <- read.table("./household_power_consumption.txt", header = TRUE,
sep = ";", na.strings = "?", nrows = 1)
#Read th... |
## Put comments here that give an overall description of what your
## functions do
## The makeCacheMatrix is a function which stores the inverse of a matrix in cache.
## When we call the cacheSolve funtin with a matrix passed as an arguement, it will check with the cache memory if the inverse already exists or notte.
... | /cachematrix.R | no_license | Debjit-Chatterjee/ProgrammingAssignment2 | R | false | false | 1,943 | r | ## Put comments here that give an overall description of what your
## functions do
## The makeCacheMatrix is a function which stores the inverse of a matrix in cache.
## When we call the cacheSolve funtin with a matrix passed as an arguement, it will check with the cache memory if the inverse already exists or notte.
... |
set_new_model("nearest_neighbor")
set_model_mode("nearest_neighbor", "classification")
set_model_mode("nearest_neighbor", "regression")
# ------------------------------------------------------------------------------
set_model_engine("nearest_neighbor", "classification", "kknn")
set_model_engine("nearest_neighbor",... | /R/nearest_neighbor_data.R | no_license | conradbm/parsnip | R | false | false | 3,853 | r |
set_new_model("nearest_neighbor")
set_model_mode("nearest_neighbor", "classification")
set_model_mode("nearest_neighbor", "regression")
# ------------------------------------------------------------------------------
set_model_engine("nearest_neighbor", "classification", "kknn")
set_model_engine("nearest_neighbor",... |
# plot4.R
library(ggplot2)
# Across the United States,
# how have emissions from coal combustion-related sources changed from 1999–2008?
#
# plot4
# argument: [path] - data set path (ex: /work/Exploratory-Data-Analysis/data)
# return: - aggregate data
plot4 <- function(path) {
# backup and replace work... | /plot4.R | no_license | daxanya1/Exploratory-Data-Analysis | R | false | false | 1,079 | r | # plot4.R
library(ggplot2)
# Across the United States,
# how have emissions from coal combustion-related sources changed from 1999–2008?
#
# plot4
# argument: [path] - data set path (ex: /work/Exploratory-Data-Analysis/data)
# return: - aggregate data
plot4 <- function(path) {
# backup and replace work... |
cualquiera <- rbinom(n = 1000000, size = 5, prob = 0.3)
# cualquiera
es_igual_a_dos <- cualquiera == 0
mean(es_igual_a_dos)
dbinom(x = 0, size = 5, prob = 0.3)
es_igual_a_dos <- cualquiera == 1
mean(es_igual_a_dos)
dbinom(x = 1, size = 5, prob = 0.3)
es_igual_a_dos <- cualquiera == 2
mean(es_igual_a_dos)
d... | /demobinomial.R | no_license | ricardomayerb/ico8306 | R | false | false | 638 | r | cualquiera <- rbinom(n = 1000000, size = 5, prob = 0.3)
# cualquiera
es_igual_a_dos <- cualquiera == 0
mean(es_igual_a_dos)
dbinom(x = 0, size = 5, prob = 0.3)
es_igual_a_dos <- cualquiera == 1
mean(es_igual_a_dos)
dbinom(x = 1, size = 5, prob = 0.3)
es_igual_a_dos <- cualquiera == 2
mean(es_igual_a_dos)
d... |
## Read data file into R.
library(lubridate)
all_data <- read.table("./exdata-data-household_power_consumption/household_power_consumption.txt", header=TRUE,
sep=";", na.strings = "?")
## Subset out only data from 2007-02-01 through 2007-02-02
all_data$Date_Time <- strptime(paste(all_data$Date, ... | /plot2.R | no_license | MelanieMaggard/ExData_Plotting1 | R | false | false | 794 | r | ## Read data file into R.
library(lubridate)
all_data <- read.table("./exdata-data-household_power_consumption/household_power_consumption.txt", header=TRUE,
sep=";", na.strings = "?")
## Subset out only data from 2007-02-01 through 2007-02-02
all_data$Date_Time <- strptime(paste(all_data$Date, ... |
# Calculate the coordinates from a design matrix D
# coords is a m by 2 matrix, each row of which corresponds to one measurement point
sampling_locs <- function(D, locs_index){
m = nrow(D)
if(length(D)>0){
coords = matrix(NA, nrow = m, ncol = 2)
for(i in 1:m){
coords[i,] = unlist(locs_index[which(D[i... | /functions/sampling_locs.R | no_license | yang221/DynamicSampling | R | false | false | 387 | r | # Calculate the coordinates from a design matrix D
# coords is a m by 2 matrix, each row of which corresponds to one measurement point
sampling_locs <- function(D, locs_index){
m = nrow(D)
if(length(D)>0){
coords = matrix(NA, nrow = m, ncol = 2)
for(i in 1:m){
coords[i,] = unlist(locs_index[which(D[i... |
library(tidyverse)
library(ICD10gm)
# Less detailed version, but is useful in case detailed version doesn't match
labs <- icd_meta_codes %>%
as_tibble() %>%
filter(year == 2018) %>% # Has different versions categorized per year, arbitrarily chose 2018
mutate(code = str_sub(icd_sub, 1, 3)) %>%
select(icd_block_... | /data-raw/icd_codes.R | no_license | bsurial/bernr | R | false | false | 1,233 | r | library(tidyverse)
library(ICD10gm)
# Less detailed version, but is useful in case detailed version doesn't match
labs <- icd_meta_codes %>%
as_tibble() %>%
filter(year == 2018) %>% # Has different versions categorized per year, arbitrarily chose 2018
mutate(code = str_sub(icd_sub, 1, 3)) %>%
select(icd_block_... |
transposer <- function(pitch, numshift) {
if (pitch == "XX") {
return(pitch)
}
PITCH_CLASS <- c("C", "d", "D", "e", "E", "F", "g", "G", "a", "A", "b", "B")
PITCH <- substr(pitch, 1, 1)
OCTAVE_MAP <- rep(as.numeric(substr(pitch, 2, 2)), length((PITCH_CLASS)))
if (numshift > 0) {
... | /Scripts/R/lib/func_transposer.R | permissive | comp-music-lab/agreement-human-automated | R | false | false | 924 | r | transposer <- function(pitch, numshift) {
if (pitch == "XX") {
return(pitch)
}
PITCH_CLASS <- c("C", "d", "D", "e", "E", "F", "g", "G", "a", "A", "b", "B")
PITCH <- substr(pitch, 1, 1)
OCTAVE_MAP <- rep(as.numeric(substr(pitch, 2, 2)), length((PITCH_CLASS)))
if (numshift > 0) {
... |
library(shiny)
source("calculations.R")
my_server <- function(input, output) {
output$initial_margin <- renderText({
c(initialMarginCalculator(input$entry_price, input$asset_quantity, input$leverage),
"USDT")
})
output$profit_without_fees <- renderText({
c(profitCalculator(input$entry_price, in... | /my_server.R | permissive | jsamyak/CryptoFuturesCalculator | R | false | false | 11,730 | r | library(shiny)
source("calculations.R")
my_server <- function(input, output) {
output$initial_margin <- renderText({
c(initialMarginCalculator(input$entry_price, input$asset_quantity, input$leverage),
"USDT")
})
output$profit_without_fees <- renderText({
c(profitCalculator(input$entry_price, in... |
# Load Daily Toronto Temperature Data (1990-2017)
# Initialize Session ####
cat("\014")
rm(list=ls())
cat("\014")
Sys.Date()
sessionInfo()
list.of.packages <- c("readxl","readr","ggplot2","plyr","tidyr","dplyr","magrittr","viridis","lubridate","grid","gridExtra")
new.packages <- list.of.packages[!(list.of.packages %i... | /TO_weather.R | no_license | eugejoh/TO_Watermain | R | false | false | 6,148 | r | # Load Daily Toronto Temperature Data (1990-2017)
# Initialize Session ####
cat("\014")
rm(list=ls())
cat("\014")
Sys.Date()
sessionInfo()
list.of.packages <- c("readxl","readr","ggplot2","plyr","tidyr","dplyr","magrittr","viridis","lubridate","grid","gridExtra")
new.packages <- list.of.packages[!(list.of.packages %i... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plots_biotmle.R
\name{volcano_biotmle}
\alias{volcano_biotmle}
\title{Volcano plot for class biotmle}
\usage{
volcano_biotmle(biotmle)
}
\arguments{
\item{biotmle}{object of class \code{biotmle} as produced by an appropriate
call to \code{bio... | /man/volcano_biotmle.Rd | permissive | guhjy/biotmle | R | false | true | 1,577 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plots_biotmle.R
\name{volcano_biotmle}
\alias{volcano_biotmle}
\title{Volcano plot for class biotmle}
\usage{
volcano_biotmle(biotmle)
}
\arguments{
\item{biotmle}{object of class \code{biotmle} as produced by an appropriate
call to \code{bio... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils_enrichment.R
\name{.filterSeqs}
\alias{.filterSeqs}
\title{Filter Sequences}
\usage{
.filterSeqs(
seqs,
maxFracN = 0.7,
minLength = 5L,
maxLength = 100000L,
verbose = FALSE
)
}
\arguments{
\item{seqs}{a \code{DNAStringSet} obj... | /man/dot-filterSeqs.Rd | no_license | shaoyoucheng/monaLisa | R | false | true | 1,148 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils_enrichment.R
\name{.filterSeqs}
\alias{.filterSeqs}
\title{Filter Sequences}
\usage{
.filterSeqs(
seqs,
maxFracN = 0.7,
minLength = 5L,
maxLength = 100000L,
verbose = FALSE
)
}
\arguments{
\item{seqs}{a \code{DNAStringSet} obj... |
setwd ("//.../Coursera/Exploratory Data Analysis/Week 4")
getwd()
install.packages("downloader")
library("downloader")
dataset_url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2FNEI_data.zip"
download(dataset_url, dest = "data.zip", mode = "wb")
unzip("data.zip", exdir = "//.../Coursera/Exploratory Data Anal... | /plot_2_Baltimore.R | no_license | xetaro/Exploratory-Data-Analysis-Course-Project-2 | R | false | false | 1,358 | r | setwd ("//.../Coursera/Exploratory Data Analysis/Week 4")
getwd()
install.packages("downloader")
library("downloader")
dataset_url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2FNEI_data.zip"
download(dataset_url, dest = "data.zip", mode = "wb")
unzip("data.zip", exdir = "//.../Coursera/Exploratory Data Anal... |
############################################################################################
## package 'secrlinear'
## getLineID.R
## 2022-11-12 separate file
############################################################################################
getLineID <- function (mask, laboffset= rep(spacing(mask)*3,... | /R/getLineID.R | no_license | cran/secrlinear | R | false | false | 1,187 | r | ############################################################################################
## package 'secrlinear'
## getLineID.R
## 2022-11-12 separate file
############################################################################################
getLineID <- function (mask, laboffset= rep(spacing(mask)*3,... |
library(xts)
file="H:\\Trading\\EATesting\\MedAvgCross\\EURJPY_1H_13.csv";
df = read.csv(file, header = TRUE , as.is = TRUE )
df$date <- as.POSIXct(df$time, format = "%d-%m-%Y %H:%M")
IndiRawXTS <- xts(x = df, order.by = df$date)
mean(df$cross)
sd(df$cross) | /MovingMedianCross/Research.R | no_license | phanigenin/Trading-Research | R | false | false | 265 | r | library(xts)
file="H:\\Trading\\EATesting\\MedAvgCross\\EURJPY_1H_13.csv";
df = read.csv(file, header = TRUE , as.is = TRUE )
df$date <- as.POSIXct(df$time, format = "%d-%m-%Y %H:%M")
IndiRawXTS <- xts(x = df, order.by = df$date)
mean(df$cross)
sd(df$cross) |
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