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 |
|---|---|---|---|---|---|---|---|---|---|
###Function to get model fit diagnostics given a STBDwDM object
#'
#' diagnostics
#'
#' Calculates diagnostic metrics using output from the \code{\link{STBDwDM}} model.
#'
#' @param obj A \code{\link{STBDwDM}} model object for which diagnostics
#' are desired from.
#'
#' @param diags A vector of character strings indi... | /fuzzedpackages/womblR/R/DIAG_diagnostics.R | no_license | akhikolla/testpackages | R | false | false | 6,775 | r | ###Function to get model fit diagnostics given a STBDwDM object
#'
#' diagnostics
#'
#' Calculates diagnostic metrics using output from the \code{\link{STBDwDM}} model.
#'
#' @param obj A \code{\link{STBDwDM}} model object for which diagnostics
#' are desired from.
#'
#' @param diags A vector of character strings indi... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/icon_sets.R
\name{icon_sets}
\alias{icon_sets}
\title{Add colored icons to cells in a column}
\usage{
icon_sets(
data,
icons = c("circle"),
colors = c("#67a9cf", "#808080", "#ef8a62"),
opacity = 1,
icon_position = "right",
icon_re... | /man/icon_sets.Rd | no_license | Arrendi/reactablefmtr | R | false | true | 3,994 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/icon_sets.R
\name{icon_sets}
\alias{icon_sets}
\title{Add colored icons to cells in a column}
\usage{
icon_sets(
data,
icons = c("circle"),
colors = c("#67a9cf", "#808080", "#ef8a62"),
opacity = 1,
icon_position = "right",
icon_re... |
## ---- out.width = "700px"------------------------------------------------
knitr::include_graphics("https://raw.githubusercontent.com/AlexiaJM/LEGIT/master/images/GxE_testing_strong.png")
## ---- out.width = "700px"------------------------------------------------
knitr::include_graphics("https://raw.githubusercon... | /data/genthat_extracted_code/LEGIT/vignettes/GxE_testing.R | no_license | surayaaramli/typeRrh | R | false | false | 2,803 | r | ## ---- out.width = "700px"------------------------------------------------
knitr::include_graphics("https://raw.githubusercontent.com/AlexiaJM/LEGIT/master/images/GxE_testing_strong.png")
## ---- out.width = "700px"------------------------------------------------
knitr::include_graphics("https://raw.githubusercon... |
library(qqman)
library(ggplot2)
library(grid)
#qq plot bayes factors with multiple window sizes:
setLayout <- function(xdim=1,ydim=1){
initmat <- c(0,0,2,0,1,3)
imat3 <- c(0,1,1,1,1,1,1,1)
imat2 <- c(0,1,1,1,1,0,0,0)
imat1 <- imat2
row1mat <- c(0,4,4,4,4,0,0,0)
row2mat <- c(0,2,2,2,2,0,0,0)
row3mat <... | /Baldwin-Brown_2017_Scripts/main_scripts/downstream_analysis_dir/qq_plot_walvee_gamma.R | no_license | jgbaldwinbrown/jgbutils | R | false | false | 10,431 | r | library(qqman)
library(ggplot2)
library(grid)
#qq plot bayes factors with multiple window sizes:
setLayout <- function(xdim=1,ydim=1){
initmat <- c(0,0,2,0,1,3)
imat3 <- c(0,1,1,1,1,1,1,1)
imat2 <- c(0,1,1,1,1,0,0,0)
imat1 <- imat2
row1mat <- c(0,4,4,4,4,0,0,0)
row2mat <- c(0,2,2,2,2,0,0,0)
row3mat <... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/weatherawhere.R
\docType{package}
\name{httr}
\alias{httr}
\alias{httr-package}
\title{\pkg{weatherawhere} is a package for gathering accurate & agriculture-specific weather data.}
\description{
\code{weatherawhere} is organised aroun... | /man/httr.Rd | no_license | yizhexu/weatherawhere | R | false | false | 690 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/weatherawhere.R
\docType{package}
\name{httr}
\alias{httr}
\alias{httr-package}
\title{\pkg{weatherawhere} is a package for gathering accurate & agriculture-specific weather data.}
\description{
\code{weatherawhere} is organised aroun... |
# Simulation Design to compare VEGAS and SKAT
| /sim.design.R | no_license | TanushreeHaldar/GeneBasedAnalysis | R | false | false | 46 | r | # Simulation Design to compare VEGAS and SKAT
|
library(regtools)
# Import data as usual...
train_values <- read.csv(
"../data/Richters_Predictor_Modeling_Earthquake_Damage_-_Train_Values.csv"
)
train_labels <- read.csv(
"../data/Richters_Predictor_Modeling_Earthquake_Damage_-_Train_Labels.csv"
)
# In order for the data to work with the regtools library, we mu... | /multinom_logic/ova-multinom.R | no_license | jesi-rgb/earthquake-analysis | R | false | false | 3,767 | r | library(regtools)
# Import data as usual...
train_values <- read.csv(
"../data/Richters_Predictor_Modeling_Earthquake_Damage_-_Train_Values.csv"
)
train_labels <- read.csv(
"../data/Richters_Predictor_Modeling_Earthquake_Damage_-_Train_Labels.csv"
)
# In order for the data to work with the regtools library, we mu... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plots.R
\name{plot_fits_gg}
\alias{plot_fits_gg}
\title{ggplot the fits data}
\usage{
plot_fits_gg(df, fit_data, limits = c(275, 400))
}
\arguments{
\item{df}{dataframe of spectroscopy data imported using caryscan package}
\item{fit_data}{da... | /man/plot_fits_gg.Rd | permissive | jonbramble/caryscan | R | false | true | 506 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plots.R
\name{plot_fits_gg}
\alias{plot_fits_gg}
\title{ggplot the fits data}
\usage{
plot_fits_gg(df, fit_data, limits = c(275, 400))
}
\arguments{
\item{df}{dataframe of spectroscopy data imported using caryscan package}
\item{fit_data}{da... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/inline_text.R
\name{inline_text.tbl_survfit}
\alias{inline_text.tbl_survfit}
\title{Report statistics from survfit tables inline}
\usage{
\method{inline_text}{tbl_survfit}(
x,
variable = NULL,
level = NULL,
pattern = NULL,
time = NU... | /man/inline_text.tbl_survfit.Rd | permissive | clara1989/gtsummary | R | false | true | 2,874 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/inline_text.R
\name{inline_text.tbl_survfit}
\alias{inline_text.tbl_survfit}
\title{Report statistics from survfit tables inline}
\usage{
\method{inline_text}{tbl_survfit}(
x,
variable = NULL,
level = NULL,
pattern = NULL,
time = NU... |
#benchmark bounded sampler
#testthat::skip_on_cran()
# define logistic model
logistic_model <- function(time, y, parms) {
with(as.list(c(y, parms)), {
dN <- r * N * (1 - N / K)
list(dN)
})
}
# set initial value for simulation
y <- c(N = 0.1)
# set parameter values
parms <- c(r = 0.1, K = 10)
# set simulat... | /sandbox/sampler_benchmarking.R | no_license | pboesu/debinfer | R | false | false | 3,753 | r | #benchmark bounded sampler
#testthat::skip_on_cran()
# define logistic model
logistic_model <- function(time, y, parms) {
with(as.list(c(y, parms)), {
dN <- r * N * (1 - N / K)
list(dN)
})
}
# set initial value for simulation
y <- c(N = 0.1)
# set parameter values
parms <- c(r = 0.1, K = 10)
# set simulat... |
library(gbm)
library(dplyr)
library(ROCR)
#Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting me... | /Code_Modeling/BOOST.R | no_license | kelsey-s/predictivemodeling_airbnb_R | R | false | false | 3,461 | r | library(gbm)
library(dplyr)
library(ROCR)
#Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting me... |
'''
m_temp<-m[!(grepl("\\.",m$`Complaint Date`)),]
m_temp<-m_temp[!(grepl("\\.",m_temp$`Complaint Resolution Date`)),]
m_temp<-m_temp[!is.na(m_temp$`Complaint Date`),]
m_temp<-m_temp[!is.na(m_temp$`Complaint Resolution Date`),]
time_compl_3<-strsplit(m_temp$`Complaint Date`, "-")
print(time_compl_3)
len<-len... | /hackapr17/t23-hackapr17/egov scripts/ClusterAnalysis_Ward.R | no_license | egovernments/Hackathon | R | false | false | 2,606 | r | '''
m_temp<-m[!(grepl("\\.",m$`Complaint Date`)),]
m_temp<-m_temp[!(grepl("\\.",m_temp$`Complaint Resolution Date`)),]
m_temp<-m_temp[!is.na(m_temp$`Complaint Date`),]
m_temp<-m_temp[!is.na(m_temp$`Complaint Resolution Date`),]
time_compl_3<-strsplit(m_temp$`Complaint Date`, "-")
print(time_compl_3)
len<-len... |
context("Testing IGMM \n")
set.seed(40)
nobs <- 1e3
yy <- rnorm(n = nobs, mean = 3, sd = 0.2)
test_that("IGMM estimates c(mu, sigma) are approx correct for a Normal distribution", {
for (tt in c("s", "h", "hh")) {
cat("Testing IGMM type ", tt, "\n")
mod <- IGMM(yy, type = tt)
# mean is approx equal
e... | /fuzzedpackages/LambertW/tests/testthat/test_IGMM.R | no_license | akhikolla/testpackages | R | false | false | 2,080 | r | context("Testing IGMM \n")
set.seed(40)
nobs <- 1e3
yy <- rnorm(n = nobs, mean = 3, sd = 0.2)
test_that("IGMM estimates c(mu, sigma) are approx correct for a Normal distribution", {
for (tt in c("s", "h", "hh")) {
cat("Testing IGMM type ", tt, "\n")
mod <- IGMM(yy, type = tt)
# mean is approx equal
e... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/XgbModel.R
\name{XgbModel}
\alias{XgbModel}
\title{Creative Modelling with Xgboost}
\usage{
XgbModel(
data,
label,
newdata,
seed,
folds,
parameter,
type = "regression",
earlystopping = 10,
print_every_n = 5,
maximize = F
)... | /man/XgbModel.Rd | no_license | horlar1/RUserLagos | R | false | true | 1,007 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/XgbModel.R
\name{XgbModel}
\alias{XgbModel}
\title{Creative Modelling with Xgboost}
\usage{
XgbModel(
data,
label,
newdata,
seed,
folds,
parameter,
type = "regression",
earlystopping = 10,
print_every_n = 5,
maximize = F
)... |
%% File Name: BIFIE.ecdf.Rd
%% File Version: 0.22
\name{BIFIE.ecdf}
\alias{BIFIE.ecdf}
\alias{summary.BIFIE.ecdf}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Empirical Distribution Function and Quantiles
}
\description{
Computes an empirical distribution function (and quantile... | /BIFIEsurvey/man/BIFIE.ecdf.Rd | no_license | akhikolla/ClusterTests | R | false | false | 3,602 | rd | %% File Name: BIFIE.ecdf.Rd
%% File Version: 0.22
\name{BIFIE.ecdf}
\alias{BIFIE.ecdf}
\alias{summary.BIFIE.ecdf}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Empirical Distribution Function and Quantiles
}
\description{
Computes an empirical distribution function (and quantile... |
\docType{data}
\name{rat}
\alias{rat}
\title{Weight gains of rats fed different diets}
\format{A data frame with 60 observations on the following 3 variables, no
NAs.
\describe{
\item{Weight.Gain}{Weight gain (grams) of rats fed the diets.}
\item{Diet.Amount}{Amount of protein in diet: 1 = High, 2 = Low.}
\item{D... | /man/rat.Rd | no_license | MichaelMBishop/granovaGG | R | false | false | 839 | rd | \docType{data}
\name{rat}
\alias{rat}
\title{Weight gains of rats fed different diets}
\format{A data frame with 60 observations on the following 3 variables, no
NAs.
\describe{
\item{Weight.Gain}{Weight gain (grams) of rats fed the diets.}
\item{Diet.Amount}{Amount of protein in diet: 1 = High, 2 = Low.}
\item{D... |
rm(list=ls())
## loading libraries
library(caret)
library(dummies)
library(plyr)
## loading data (edit the paths)
setwd("C:/Users/Abhilash/Desktop/Main project/Restaurant prediction kaggle")
#loading the data
train<-read.csv("train.csv",header = T,sep=',',stringsAsFactors=F)
test<-read.csv("test.csv",h... | /Abhilash_rangu.R | no_license | Abhilashrangu8/My-first-repository | R | false | false | 9,917 | r | rm(list=ls())
## loading libraries
library(caret)
library(dummies)
library(plyr)
## loading data (edit the paths)
setwd("C:/Users/Abhilash/Desktop/Main project/Restaurant prediction kaggle")
#loading the data
train<-read.csv("train.csv",header = T,sep=',',stringsAsFactors=F)
test<-read.csv("test.csv",h... |
#' estimateG
#'
#' Function to estimate propensity score
#'
#' @param A A vector of binary treatment assignment (assumed to be equal to 0 or
#' 1)
#' @param DeltaY Indicator of missing outcome (assumed to be equal to 0 if
#' missing 1 if observed)
#' @param DeltaA Indicator of missing treatment (assumed to be equal t... | /estimate.R | permissive | benkeser/TestRepo | R | false | false | 63,197 | r | #' estimateG
#'
#' Function to estimate propensity score
#'
#' @param A A vector of binary treatment assignment (assumed to be equal to 0 or
#' 1)
#' @param DeltaY Indicator of missing outcome (assumed to be equal to 0 if
#' missing 1 if observed)
#' @param DeltaA Indicator of missing treatment (assumed to be equal t... |
# User options
use_precompile <- FALSE
use_gpu <- FALSE
use_mingw <- FALSE
if (.Machine$sizeof.pointer != 8L) {
stop("LightGBM only supports 64-bit R, please check the version of R and Rtools.")
}
R_int_UUID <- .Internal(internalsID())
R_ver <- as.double(R.Version()$major) + as.double(R.Version()$minor) / 10.0
if ... | /R-package/src/install.libs.R | permissive | hoshinory/LightGBM | R | false | false | 7,591 | r | # User options
use_precompile <- FALSE
use_gpu <- FALSE
use_mingw <- FALSE
if (.Machine$sizeof.pointer != 8L) {
stop("LightGBM only supports 64-bit R, please check the version of R and Rtools.")
}
R_int_UUID <- .Internal(internalsID())
R_ver <- as.double(R.Version()$major) + as.double(R.Version()$minor) / 10.0
if ... |
testlist <- list(barrier = 0, ben = numeric(0), fee = 0, penalty = numeric(0), spot = c(8.3138050000614e-275, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, 5.82508648364645e-316, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0))
result <- do.call(valuer::calc_account,testlist)
str(result) | /valuer/inst/testfiles/calc_account/libFuzzer_calc_account/calc_account_valgrind_files/1616985927-test.R | no_license | akhikolla/updatedatatype-list4 | R | false | false | 296 | r | testlist <- list(barrier = 0, ben = numeric(0), fee = 0, penalty = numeric(0), spot = c(8.3138050000614e-275, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, 5.82508648364645e-316, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0))
result <- do.call(valuer::calc_account,testlist)
str(result) |
# vim: noai:ts=2:sw=2
## recursive function that transforms the kraken dataframe into a cascading list
build_kraken_tree <- function(report) {
if (nrow(report) == 0 || nrow(report) == 1) {
# this should only happen if the original input to the function has a size <= 1
return(list(report))
}
## select th... | /R/datainput-read_report.R | no_license | phac-nml/pavian | R | false | false | 21,376 | r | # vim: noai:ts=2:sw=2
## recursive function that transforms the kraken dataframe into a cascading list
build_kraken_tree <- function(report) {
if (nrow(report) == 0 || nrow(report) == 1) {
# this should only happen if the original input to the function has a size <= 1
return(list(report))
}
## select th... |
#' Project Template
#'
#' Generate a project template to increase efficiency.
#'
#' @param project A character vector of the project name.
#' @param path The path to where the project should be created. Default is the
#' current working directory.
#' @param open logical. If \code{TRUE} the project will be opened i... | /R/new_project.R | no_license | cran/qdap | R | false | false | 14,055 | r | #' Project Template
#'
#' Generate a project template to increase efficiency.
#'
#' @param project A character vector of the project name.
#' @param path The path to where the project should be created. Default is the
#' current working directory.
#' @param open logical. If \code{TRUE} the project will be opened i... |
files <- list.files("lessons", pattern = "*.Rmd$", full.names = TRUE)
# purrr::walk(files, rmarkdown::render, output_format = "html_document")
for (f in files) rmarkdown::render(f)
files_html <- stringr::str_replace_all(files, ".Rmd", ".html")
purrr::walk(c(files,files_html), fs::file_copy,
new_path = "... | /R/render_site.R | no_license | d-bohn/psych-301 | R | false | false | 381 | r | files <- list.files("lessons", pattern = "*.Rmd$", full.names = TRUE)
# purrr::walk(files, rmarkdown::render, output_format = "html_document")
for (f in files) rmarkdown::render(f)
files_html <- stringr::str_replace_all(files, ".Rmd", ".html")
purrr::walk(c(files,files_html), fs::file_copy,
new_path = "... |
#loading libraries
library(plyr)
library(dplyr)
library(ggplot2)
#---------------------------------------------------------------------------------------------------------------------
#Reading data set
data <- read.csv("data/DOHMH_NYC.csv", na.strings = c("NA","Not Applicable"))
#--------------------------------... | /Project.R | no_license | manuj005/nyc_restaurant_inspection | R | false | false | 9,158 | r | #loading libraries
library(plyr)
library(dplyr)
library(ggplot2)
#---------------------------------------------------------------------------------------------------------------------
#Reading data set
data <- read.csv("data/DOHMH_NYC.csv", na.strings = c("NA","Not Applicable"))
#--------------------------------... |
\name{get.opt.k}
\alias{get.opt.k}
\title{Optimal temporal aggregation level}
\description{Find optimal temporal aggregation level for AR(1), MA(1), ARMA(1,1).}
\usage{
get.opt.k(y,m=12,type=c("ar","ma","arma"))
}
\arguments{
\item{y}{
Time series (ts object).
}
\item{m}{
Maximum temporal aggregation le... | /man/get.opt.k.Rd | no_license | edergsc/TStools | R | false | false | 894 | rd | \name{get.opt.k}
\alias{get.opt.k}
\title{Optimal temporal aggregation level}
\description{Find optimal temporal aggregation level for AR(1), MA(1), ARMA(1,1).}
\usage{
get.opt.k(y,m=12,type=c("ar","ma","arma"))
}
\arguments{
\item{y}{
Time series (ts object).
}
\item{m}{
Maximum temporal aggregation le... |
\name{this_month}
\alias{this_month}
\title{
Start and end of month
}
\description{
Defines first and last date in month
}
\usage{
this_month(x = Sys.Date(),
part = getOption("timeperiodsR.parts"))
}
\arguments{
\item{x}{Date object}
\item{part}{Part of period you need to receive, one of "a... | /man/this_month.Rd | no_license | selesnow/timeperiodsR | R | false | false | 1,346 | rd | \name{this_month}
\alias{this_month}
\title{
Start and end of month
}
\description{
Defines first and last date in month
}
\usage{
this_month(x = Sys.Date(),
part = getOption("timeperiodsR.parts"))
}
\arguments{
\item{x}{Date object}
\item{part}{Part of period you need to receive, one of "a... |
# Format Flora do Brasil first
##loads packages----
library(dplyr)
library(flora)
library(readr)
#Downloads data from FdB----
#library("downloader")
#pag <- "http://ipt.jbrj.gov.br/jbrj/archive.do?r=lista_especies_flora_brasil"
#download(url = pag, destfile = "iptflora")
#unzip("iptflora",exdir = "./ipt")
#reads form... | /scripts/1 flora.R | no_license | AndreaSanchezTapia/CNCFlora_IUCN_LC | R | false | false | 1,944 | r | # Format Flora do Brasil first
##loads packages----
library(dplyr)
library(flora)
library(readr)
#Downloads data from FdB----
#library("downloader")
#pag <- "http://ipt.jbrj.gov.br/jbrj/archive.do?r=lista_especies_flora_brasil"
#download(url = pag, destfile = "iptflora")
#unzip("iptflora",exdir = "./ipt")
#reads form... |
#' Generate a forest plot from a meta-analysis
#'
#' @param model a single \code{\link[metafor]{rma}} object or a \code{list} of them
#' @param study_labels a character vector of study labels or list of character vectors the same length as \code{model}
#' @param model_label a single model label or character vector of m... | /R/forest_rma.R | no_license | zhangyupisa/forestmodel | R | false | false | 9,180 | r | #' Generate a forest plot from a meta-analysis
#'
#' @param model a single \code{\link[metafor]{rma}} object or a \code{list} of them
#' @param study_labels a character vector of study labels or list of character vectors the same length as \code{model}
#' @param model_label a single model label or character vector of m... |
#Atenção: Alterar Diretório
setwd("C:/...")
options(scipen=999)
#Leitura da Base de Dados
df <- read.csv("df.csv")
#Verificar variáveis
names(df)
# Matriz de Gráfico de Dispersão
#Matriz de Scatter Plot
library(GGally)
ggpairs(Imobiliario, title="correlogram with ggpairs()")
#Regressão Linear Múltipla
#Modelo de R... | /regressao.R | no_license | nelson-ewert/calculadora-aluguel | R | false | false | 466 | r | #Atenção: Alterar Diretório
setwd("C:/...")
options(scipen=999)
#Leitura da Base de Dados
df <- read.csv("df.csv")
#Verificar variáveis
names(df)
# Matriz de Gráfico de Dispersão
#Matriz de Scatter Plot
library(GGally)
ggpairs(Imobiliario, title="correlogram with ggpairs()")
#Regressão Linear Múltipla
#Modelo de R... |
#' read_DEVTRANS
#'
#' @describeIn read_CEIDARS Read DEVTRANS-formatted file
#'
#' @export
read_DEVTRANS <- function (
path,
...
) {
DEVTRANS_cols <- readr::cols(
TRANS_ID = col_character(),
CO = col_integer(),
FACID = col_integer(),
AB = col_character(),
DIS = col_character(),
ACTION = c... | /R/read_DEVTRANS.R | no_license | BAAQMD/CEIDARS | R | false | false | 1,100 | r | #' read_DEVTRANS
#'
#' @describeIn read_CEIDARS Read DEVTRANS-formatted file
#'
#' @export
read_DEVTRANS <- function (
path,
...
) {
DEVTRANS_cols <- readr::cols(
TRANS_ID = col_character(),
CO = col_integer(),
FACID = col_integer(),
AB = col_character(),
DIS = col_character(),
ACTION = c... |
#' Mexican power network
#'
#' A network of 11 core members of the 1990s Mexican power elite (Knoke 2017),
#' three of which were successively elected presidents of Mexico:
#' José López Portillo (1976-82), Miguel de la Madrid (1982-88), and Carlos Salinas de Gortari (1988-94,
#' who was also the son of another core... | /R/data_mexicanpower.R | permissive | toshitaka-izumi/migraph | R | false | false | 997 | r | #' Mexican power network
#'
#' A network of 11 core members of the 1990s Mexican power elite (Knoke 2017),
#' three of which were successively elected presidents of Mexico:
#' José López Portillo (1976-82), Miguel de la Madrid (1982-88), and Carlos Salinas de Gortari (1988-94,
#' who was also the son of another core... |
#' calculates map curve
#'
#' @keywords internal
calcular.map <- function(i.datos) {
datos <- as.vector(as.matrix(i.datos))
semanas <- length(datos)
maxsumasemanas <- array(dim = c(semanas, 5))
for (s in 1:semanas) {
sumasemanas <- numeric()
for (i in 1:(semanas + 1 - s)) {
sumasemanas <- c(sumase... | /R/calcular.map.R | no_license | lozalojo/mem | R | false | false | 839 | r | #' calculates map curve
#'
#' @keywords internal
calcular.map <- function(i.datos) {
datos <- as.vector(as.matrix(i.datos))
semanas <- length(datos)
maxsumasemanas <- array(dim = c(semanas, 5))
for (s in 1:semanas) {
sumasemanas <- numeric()
for (i in 1:(semanas + 1 - s)) {
sumasemanas <- c(sumase... |
#' Function to assign properties to an expression matrix
#'
#' This is a function to assign stromal property and TNBCType generative property levels to a TNBC dataset
#' @param ESet An ExpressionSet object. Rows correspond to genes, columns to samples. If there are genes with multiple probes, they will be collapsed to ... | /R/assign.property.R | no_license | smisaleh/STROMA4 | R | false | false | 4,782 | r | #' Function to assign properties to an expression matrix
#'
#' This is a function to assign stromal property and TNBCType generative property levels to a TNBC dataset
#' @param ESet An ExpressionSet object. Rows correspond to genes, columns to samples. If there are genes with multiple probes, they will be collapsed to ... |
PE <- function (U, b)
{
if (missing(U))
stop("The membership degree matrix U must be given")
if (is.null(U))
stop("The membership degree matrix U is empty")
U=as.matrix(U)
if (any(is.na(U)))
stop("The membership degree matrix U must not contain NA values")
if (!is.numeric(U))
... | /R/PE_mod.R | no_license | cran/fclust | R | false | false | 793 | r | PE <- function (U, b)
{
if (missing(U))
stop("The membership degree matrix U must be given")
if (is.null(U))
stop("The membership degree matrix U is empty")
U=as.matrix(U)
if (any(is.na(U)))
stop("The membership degree matrix U must not contain NA values")
if (!is.numeric(U))
... |
#' Affichage LaTeX d'un systeme d'equations lineaires (SEL)
#'
#' \code{sel2latex} retourne un vecteur de caracteres qui contient le code LaTeX permettant d'ecrire le SEL forme de la matrice \code{A}
#' et de la matrice \code{B}.
#' Nous pouvons choisir la facon d'afficher le SEL. Nous pouvons afficher des nombres ent... | /R/sel2latex.R | no_license | desautm/linalgr | R | false | false | 6,040 | r | #' Affichage LaTeX d'un systeme d'equations lineaires (SEL)
#'
#' \code{sel2latex} retourne un vecteur de caracteres qui contient le code LaTeX permettant d'ecrire le SEL forme de la matrice \code{A}
#' et de la matrice \code{B}.
#' Nous pouvons choisir la facon d'afficher le SEL. Nous pouvons afficher des nombres ent... |
# WOCAT: COST AND BENEFIT DATABASE
# FINAL CLEAN SPREADSHEET
library(here)
library(tidyverse)
library(lubridate)
#library(sjlabelled)
library(labelled)
library(codebook)
# MERGE ALL DATASETS
filename = here::here("03_processed_data","03_Data_general.rds")
Data_general<-readRDS(filename)
filename = here::here... | /01_code/06_Final_SLM_tech_data.R | no_license | Nabeehz/wocat_project | R | false | false | 8,735 | r | # WOCAT: COST AND BENEFIT DATABASE
# FINAL CLEAN SPREADSHEET
library(here)
library(tidyverse)
library(lubridate)
#library(sjlabelled)
library(labelled)
library(codebook)
# MERGE ALL DATASETS
filename = here::here("03_processed_data","03_Data_general.rds")
Data_general<-readRDS(filename)
filename = here::here... |
setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source("../../scripts/h2o-r-test-setup.R")
##
# Set levels of a factor column
##
test.setLevels <- function() {
hex <- as.h2o(iris)
hex.species.copy <- hex$Species
species.orig <- h2o.levels(hex$Species)
Log.info("Tests in-place modifi... | /h2o-r/tests/testdir_misc/runit_revalue.R | permissive | h2oai/h2o-3 | R | false | false | 1,023 | r | setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
source("../../scripts/h2o-r-test-setup.R")
##
# Set levels of a factor column
##
test.setLevels <- function() {
hex <- as.h2o(iris)
hex.species.copy <- hex$Species
species.orig <- h2o.levels(hex$Species)
Log.info("Tests in-place modifi... |
# Problem 8.2.4 - Fold-Fulkerson algorithm (not counted)
library(optrees)
nodes <- 1:4
arcs <- matrix(c(1, 2, 2,
1, 3, 1,
2, 3, -2,
2, 4, 1,
3, 4, 1),
ncol = 3,
byrow = T)
# answer obtained
getShortestPathTree(nodes,
... | /Coding 2/assignment2_final.txt | no_license | virtuoso98/ysc2254-modelling | R | false | false | 4,227 | txt | # Problem 8.2.4 - Fold-Fulkerson algorithm (not counted)
library(optrees)
nodes <- 1:4
arcs <- matrix(c(1, 2, 2,
1, 3, 1,
2, 3, -2,
2, 4, 1,
3, 4, 1),
ncol = 3,
byrow = T)
# answer obtained
getShortestPathTree(nodes,
... |
#!/usr/bin/env Rscript
###################################################################
# This file is part of RiboWave.
# RiboWave is powerful Ribo-seq analysis tool that is able to
# denoise the Ribo-seq data and serve for multiple functions.
#
# RiboWave can be used for multiple purposes:
# 1... | /psite_1nt_wholeReads.R | no_license | xanthexu/ribosome-profiling | R | false | false | 1,554 | r | #!/usr/bin/env Rscript
###################################################################
# This file is part of RiboWave.
# RiboWave is powerful Ribo-seq analysis tool that is able to
# denoise the Ribo-seq data and serve for multiple functions.
#
# RiboWave can be used for multiple purposes:
# 1... |
# Example 16 Chapter 6 Page no.: 187
# Bairstow's method
#Given function
f <- function(x) {
(x^3)+x+10
}
#Given values
u= 1.8
v= -1
es=1
#%
n=4
count=1
ear=100
eas=100
a<-c(10,1,0,1)
b<-matrix(0,n)
c<-matrix(0,n)
while ((ear>es) & (eas>es)){
b[n]=a[n]
b[n-1]=a[n-1]+u*b... | /Numerical_Methods_by_E_Balaguruswamy/CH6/EX6.16/Ex6_16.R | permissive | prashantsinalkar/R_TBC_Uploads | R | false | false | 977 | r | # Example 16 Chapter 6 Page no.: 187
# Bairstow's method
#Given function
f <- function(x) {
(x^3)+x+10
}
#Given values
u= 1.8
v= -1
es=1
#%
n=4
count=1
ear=100
eas=100
a<-c(10,1,0,1)
b<-matrix(0,n)
c<-matrix(0,n)
while ((ear>es) & (eas>es)){
b[n]=a[n]
b[n-1]=a[n-1]+u*b... |
data<-read.table("household_power_consumption.txt",header=TRUE,sep=";", colClasses=c("character","character","double", "double","double","double","double","double","numeric"), na.strings="?")
data_sub<-subset(data, data$Date=="1/2/2007"|data$Date=="2/2/2007")
png('./Desktop plot1.png')
hist(data_sub$Global_active_power... | /ExData_Plotting1-master/plot1.R | no_license | luw517/Data-Science-Specialization | R | false | false | 425 | r | data<-read.table("household_power_consumption.txt",header=TRUE,sep=";", colClasses=c("character","character","double", "double","double","double","double","double","numeric"), na.strings="?")
data_sub<-subset(data, data$Date=="1/2/2007"|data$Date=="2/2/2007")
png('./Desktop plot1.png')
hist(data_sub$Global_active_power... |
library(SNFtool)
### Name: Data2
### Title: Data2
### Aliases: Data2
### Keywords: datasets
### ** Examples
data(Data2)
| /data/genthat_extracted_code/SNFtool/examples/Data2.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 127 | r | library(SNFtool)
### Name: Data2
### Title: Data2
### Aliases: Data2
### Keywords: datasets
### ** Examples
data(Data2)
|
# Project: Open Data of the Black Diaspora
# Dataset: Emancipators
# Source: Emigrants to Liberia Project, Virginia Center for Digital History
# http://www.vcdh.virginia.edu/liberia/index.php?page=Resources§ion=Search%20Emancipators&result=yes
#----packages----
library(rvest)
library(pryr)
library(dplyr)
library(... | /Virginia Emigrants to Liberia/emancipators.R | no_license | maniacalwhistle/diaspora-data | R | false | false | 1,588 | r | # Project: Open Data of the Black Diaspora
# Dataset: Emancipators
# Source: Emigrants to Liberia Project, Virginia Center for Digital History
# http://www.vcdh.virginia.edu/liberia/index.php?page=Resources§ion=Search%20Emancipators&result=yes
#----packages----
library(rvest)
library(pryr)
library(dplyr)
library(... |
library(lulcc)
### Name: FigureOfMerit
### Title: Create a FigureOfMerit object
### Aliases: FigureOfMerit FigureOfMerit,RasterLayer-method
### FigureOfMerit,ThreeMapComparison-method
### ** Examples
## see lulcc-package examples
| /data/genthat_extracted_code/lulcc/examples/FigureOfMerit.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 240 | r | library(lulcc)
### Name: FigureOfMerit
### Title: Create a FigureOfMerit object
### Aliases: FigureOfMerit FigureOfMerit,RasterLayer-method
### FigureOfMerit,ThreeMapComparison-method
### ** Examples
## see lulcc-package examples
|
library(MKmisc)
### Name: IQrange
### Title: The Interquartile Range
### Aliases: IQrange sIQR
### Keywords: univar robust distribution
### ** Examples
IQrange(rivers)
## identical to
IQR(rivers)
## other quantile algorithms
IQrange(rivers, type = 4)
IQrange(rivers, type = 5)
## standardized IQR
sIQR(rivers)
##... | /data/genthat_extracted_code/MKmisc/examples/IQrange.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 435 | r | library(MKmisc)
### Name: IQrange
### Title: The Interquartile Range
### Aliases: IQrange sIQR
### Keywords: univar robust distribution
### ** Examples
IQrange(rivers)
## identical to
IQR(rivers)
## other quantile algorithms
IQrange(rivers, type = 4)
IQrange(rivers, type = 5)
## standardized IQR
sIQR(rivers)
##... |
library(cubing)
### Name: invCube
### Title: Calculate Inverse Cube
### Aliases: invCube
### Keywords: manip
### ** Examples
aCube <- getCubieCube("Tetris")
is.solved(aCube %v% invCube(aCube))
is.solved(invCube(aCube) %v% aCube)
## Not run: plot(aCube)
## Not run: plot(invCube(aCube))
## Not run: plot3D(aCube)
## ... | /data/genthat_extracted_code/cubing/examples/invCube.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 355 | r | library(cubing)
### Name: invCube
### Title: Calculate Inverse Cube
### Aliases: invCube
### Keywords: manip
### ** Examples
aCube <- getCubieCube("Tetris")
is.solved(aCube %v% invCube(aCube))
is.solved(invCube(aCube) %v% aCube)
## Not run: plot(aCube)
## Not run: plot(invCube(aCube))
## Not run: plot3D(aCube)
## ... |
###########################################################################
#' Load a report file into the dataframe
#' @param file A file of a report file, in .txt or .csv format.
#' @return a data frame of the report file
#' @examples
#' file <- paste(system.file("files",package="iSwathX"),"Report_file.txt",sep="/")... | /readReportFile.R | no_license | znoor/iSwathX | R | false | false | 887 | r | ###########################################################################
#' Load a report file into the dataframe
#' @param file A file of a report file, in .txt or .csv format.
#' @return a data frame of the report file
#' @examples
#' file <- paste(system.file("files",package="iSwathX"),"Report_file.txt",sep="/")... |
## Put comments here that give an overall description of what your
## functions do
# This returns a list of functions that can cache the inverse of a matrix
# set(X) :: sets the matrix
# get() :: returns the matrix
# setInverse(i) :: sets the inverse value
# getInverse() :: gets the inverse value
# this assumes the ... | /cachematrix.R | no_license | ericfarng/ProgrammingAssignment2 | R | false | false | 1,582 | r | ## Put comments here that give an overall description of what your
## functions do
# This returns a list of functions that can cache the inverse of a matrix
# set(X) :: sets the matrix
# get() :: returns the matrix
# setInverse(i) :: sets the inverse value
# getInverse() :: gets the inverse value
# this assumes the ... |
library("IMFData", lib.loc="~/R/x86_64-pc-linux-gnu-library/3.5")
databaseID <- "IFS"
startdate = "1900-01-01"
enddate = "2016-12-31"
checkquery = FALSE
country_list <- c("") # all countries
### Indicators List
## search for indicators here: http://data.imf.org/?sk=4C514D48-B6BA-49ED-8AB9-52B0C1A0179B&sId=14091512... | /pulling_data/IMF/pulling_merging_data.R | no_license | Matt-Brigida/IMF_World_Bank_Data | R | false | false | 3,133 | r |
library("IMFData", lib.loc="~/R/x86_64-pc-linux-gnu-library/3.5")
databaseID <- "IFS"
startdate = "1900-01-01"
enddate = "2016-12-31"
checkquery = FALSE
country_list <- c("") # all countries
### Indicators List
## search for indicators here: http://data.imf.org/?sk=4C514D48-B6BA-49ED-8AB9-52B0C1A0179B&sId=14091512... |
# Test IKS aquastar nouvelle generation
library(econum)
#ls /dev/cu*
options(iks.port = "/dev/cu.usbserial-FTB3O67T")
iks.open()
iks.getAll()
iks.getName()
iks.getData()
iks.getConfig()
options(debug.IKS = TRUE)
options(debug.IKS = FALSE)
iks.close()
| /inst/test/test.iks.R | permissive | EcoNum/econum | R | false | false | 253 | r | # Test IKS aquastar nouvelle generation
library(econum)
#ls /dev/cu*
options(iks.port = "/dev/cu.usbserial-FTB3O67T")
iks.open()
iks.getAll()
iks.getName()
iks.getData()
iks.getConfig()
options(debug.IKS = TRUE)
options(debug.IKS = FALSE)
iks.close()
|
#' Make volcano plot
#'
#' @param data data frame containing stats
#' @param effect_var variable name for effect size (x-axis)
#' @param p_var p value - variable name for y-axis
#' @param q_var q value--when specified, defaults to highlighting points that pass q_thresh
#' @param q_thresh q value threshold for highlight... | /R/volcano_plot.R | no_license | broadinstitute/cdsr_plots | R | false | false | 4,543 | r | #' Make volcano plot
#'
#' @param data data frame containing stats
#' @param effect_var variable name for effect size (x-axis)
#' @param p_var p value - variable name for y-axis
#' @param q_var q value--when specified, defaults to highlighting points that pass q_thresh
#' @param q_thresh q value threshold for highlight... |
##This script reads data from "household_power_consumption.txt" and plots measurements from
## three sub meters vs time. The file "household_power_consumption.txt" must be in the same working directory.
## Initialize a data frame and read the text file
data <- data.frame()
data <- read.csv("household_power_consumption... | /plot3.R | no_license | jordanschmidt/ExData_Plotting1 | R | false | false | 1,338 | r | ##This script reads data from "household_power_consumption.txt" and plots measurements from
## three sub meters vs time. The file "household_power_consumption.txt" must be in the same working directory.
## Initialize a data frame and read the text file
data <- data.frame()
data <- read.csv("household_power_consumption... |
cat("\014") # Clear your console
rm(list = ls()) #clear your environment
########################## Load in header file ######################## #
source(file.path("C:/Users/Nick/git/of-dollars-and-data/header.R"))
########################## Load in Libraries ########################## #
library(dplyr)
library(strin... | /build/05-build-bls-occupational-employment.R | no_license | joyeung/of-dollars-and-data | R | false | false | 2,416 | r | cat("\014") # Clear your console
rm(list = ls()) #clear your environment
########################## Load in header file ######################## #
source(file.path("C:/Users/Nick/git/of-dollars-and-data/header.R"))
########################## Load in Libraries ########################## #
library(dplyr)
library(strin... |
\name{gasAcu1.nscanGene.LENGTH}
\docType{data}
\alias{gasAcu1.nscanGene.LENGTH}
\title{Transcript length data for the organism gasAcu}
\description{gasAcu1.nscanGene.LENGTH is an R object which maps transcripts to the length (in bp) of their mature mRNA transcripts. Where available, it will also provide the mapping be... | /man/gasAcu1.nscanGene.LENGTH.Rd | no_license | nadiadavidson/geneLenDataBase | R | false | false | 759 | rd | \name{gasAcu1.nscanGene.LENGTH}
\docType{data}
\alias{gasAcu1.nscanGene.LENGTH}
\title{Transcript length data for the organism gasAcu}
\description{gasAcu1.nscanGene.LENGTH is an R object which maps transcripts to the length (in bp) of their mature mRNA transcripts. Where available, it will also provide the mapping be... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/addtables.R
\name{addtablesUI}
\alias{addtablesUI}
\title{addtablesUI}
\usage{
addtablesUI(id, M)
}
\arguments{
\item{id}{is caller id}
\item{M}{is the meta data connection structure}
}
\description{
UI for adding tables to 'cuborg' data war... | /man/addtablesUI.Rd | no_license | byadu/modcubingest | R | false | true | 329 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/addtables.R
\name{addtablesUI}
\alias{addtablesUI}
\title{addtablesUI}
\usage{
addtablesUI(id, M)
}
\arguments{
\item{id}{is caller id}
\item{M}{is the meta data connection structure}
}
\description{
UI for adding tables to 'cuborg' data war... |
tar_test("rds update_object()", {
x <- target_init(name = "abc", expr = quote(a), format = "rds")
builder_update_build(x, tmpenv(a = "123"))
builder_update_paths(x, path_store_default())
expect_false(file.exists(x$store$file$path))
expect_true(is.na(x$store$file$hash))
store_update_stage_early(x$store, "abc... | /tests/testthat/test-class_rds.R | permissive | billdenney/targets | R | false | false | 1,504 | r | tar_test("rds update_object()", {
x <- target_init(name = "abc", expr = quote(a), format = "rds")
builder_update_build(x, tmpenv(a = "123"))
builder_update_paths(x, path_store_default())
expect_false(file.exists(x$store$file$path))
expect_true(is.na(x$store$file$hash))
store_update_stage_early(x$store, "abc... |
#' Wrapper function for summarizing the outputs from DreamAI_bagging
#'
#' @param method a vector of imputation methods: ("KNN", "MissForest", "ADMIN", "Brinn", "SpectroFM, "RegImpute", "Ensemble"). This vector should be a subset or equal to the vector out in DreamAI_bagging.
#' @param nNodes number of parallel proc... | /Code/R/wrapper.R | no_license | schatterjee-lilly/DreamAI | R | false | false | 6,754 | r | #' Wrapper function for summarizing the outputs from DreamAI_bagging
#'
#' @param method a vector of imputation methods: ("KNN", "MissForest", "ADMIN", "Brinn", "SpectroFM, "RegImpute", "Ensemble"). This vector should be a subset or equal to the vector out in DreamAI_bagging.
#' @param nNodes number of parallel proc... |
#STEP 6: PLOT 4
#FIRST I OPEN DEVICE, AFTER I MAKE THE PLOTS CONSECUTIVELY (TELLING THAT I WANT TWO PLOTS PER LINE AND PER COLUMN- par(mfrow=c(2,2)))
#AND SET THE LEGEND. FINALLY, I CLOSE DEVICE.
png("plot4.png",width=480,height=480,units="px")
par(mfrow=c(2,2))
plot(muestra$Datetime, muestra$Global_active_power,type=... | /plot4.R | no_license | Edurnita/ExData_Plotting1 | R | false | false | 921 | r | #STEP 6: PLOT 4
#FIRST I OPEN DEVICE, AFTER I MAKE THE PLOTS CONSECUTIVELY (TELLING THAT I WANT TWO PLOTS PER LINE AND PER COLUMN- par(mfrow=c(2,2)))
#AND SET THE LEGEND. FINALLY, I CLOSE DEVICE.
png("plot4.png",width=480,height=480,units="px")
par(mfrow=c(2,2))
plot(muestra$Datetime, muestra$Global_active_power,type=... |
#Read the files
NEI <- readRDS("./summarySCC_PM25.rds")
SCC <- readRDS("./Source_Classification_Code.rds")
#Subset the data appropriately
subset <- NEI[NEI$fips == "24510", ]
#Specify global graphics parameter(here: the margins for the plot)
par("mar"=c(5.1, 4.5, 4.1, 2.1))
#Launch the graphics device(file devic... | /plot2.R | no_license | devvarya/ExData_Plotting2 | R | false | false | 767 | r | #Read the files
NEI <- readRDS("./summarySCC_PM25.rds")
SCC <- readRDS("./Source_Classification_Code.rds")
#Subset the data appropriately
subset <- NEI[NEI$fips == "24510", ]
#Specify global graphics parameter(here: the margins for the plot)
par("mar"=c(5.1, 4.5, 4.1, 2.1))
#Launch the graphics device(file devic... |
data <- read.table("household_power_consumption.txt", header=TRUE, na.strings="?", sep=";")
data <- data[(data$Date=="1/2/2007" | data$Date=="2/2/2007" ), ]
data$DateTime<-as.POSIXct(paste(data$Date,data$Time), format="%d/%m/%Y %H:%M:%S")
#plot4
par(mfrow=c(2,2), mar=c(4,5,2,1), oma=c(0,0,2,0))
with(data, {
plot(Glo... | /plot4.R | no_license | bairdstar/ExData_Plotting1 | R | false | false | 997 | r | data <- read.table("household_power_consumption.txt", header=TRUE, na.strings="?", sep=";")
data <- data[(data$Date=="1/2/2007" | data$Date=="2/2/2007" ), ]
data$DateTime<-as.POSIXct(paste(data$Date,data$Time), format="%d/%m/%Y %H:%M:%S")
#plot4
par(mfrow=c(2,2), mar=c(4,5,2,1), oma=c(0,0,2,0))
with(data, {
plot(Glo... |
require(dplyr)
require(tidyr)
require(cowplot)
require(ggplot2)
require(xtable)
require(sqldf)
require(stringr)
require(rwetools)
##-----------------------------------------------------------------------------
## LOAD INTERMACS DATA
##-------------------------------------------------------------... | /sql_summary_stats.R | no_license | sallytt22/intermacs_database | R | false | false | 21,511 | r | require(dplyr)
require(tidyr)
require(cowplot)
require(ggplot2)
require(xtable)
require(sqldf)
require(stringr)
require(rwetools)
##-----------------------------------------------------------------------------
## LOAD INTERMACS DATA
##-------------------------------------------------------------... |
####################################################
# Author: Eric Tulowetzke, eric.tulowetzke@jacks.sdstate.edu
# Lab: Ge Lab
# R version 4.0.5
# Project: iDEP v93
# File: gene_id_page_ser.R
# Purpose of file:server logic for second tab i.e. Gene ID Examples
# Allow users view example of database
# Start data: 06-06... | /shinyapps/idep93/gene_id_page_ser.R | no_license | iDEP-SDSU/idep | R | false | false | 7,030 | r | ####################################################
# Author: Eric Tulowetzke, eric.tulowetzke@jacks.sdstate.edu
# Lab: Ge Lab
# R version 4.0.5
# Project: iDEP v93
# File: gene_id_page_ser.R
# Purpose of file:server logic for second tab i.e. Gene ID Examples
# Allow users view example of database
# Start data: 06-06... |
# @file Plots.R
#
# Copyright 2018 Observational Health Data Sciences and Informatics
#
# This file is part of MethodEvaluation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http:... | /R/Plots.R | permissive | jamieweaver/MethodEvaluation | R | false | false | 7,298 | r | # @file Plots.R
#
# Copyright 2018 Observational Health Data Sciences and Informatics
#
# This file is part of MethodEvaluation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http:... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/util.R
\name{SigmaL2}
\alias{SigmaL2}
\title{SigmaL2}
\usage{
SigmaL2(zlab, listZonePoint, tabVal, surfVoronoi)
}
\arguments{
\item{zlab}{list with zone numbers for each zone label}
\item{listZonePoint}{list of indices of data points within ... | /man/SigmaL2.Rd | no_license | hazaeljones/geozoning | R | false | true | 1,362 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/util.R
\name{SigmaL2}
\alias{SigmaL2}
\title{SigmaL2}
\usage{
SigmaL2(zlab, listZonePoint, tabVal, surfVoronoi)
}
\arguments{
\item{zlab}{list with zone numbers for each zone label}
\item{listZonePoint}{list of indices of data points within ... |
appendUnitTET <- function(Z, matches) {
# Split sample
treatedSample <- Z[which(Z[,2] == 1),]
controlSample <- Z[which(Z[,2] == 0),]
# Get N1 and N0
n1 <- length(treatedSample[,1])
n0 <- length(controlSample[,1])
# First, I want to generate counterfactual outcomes
# for each treated unit.
# T... | /R Code/Rewrite/appendUnitTET.R | no_license | njulius/wild-bootstrap-matching | R | false | false | 1,505 | r | appendUnitTET <- function(Z, matches) {
# Split sample
treatedSample <- Z[which(Z[,2] == 1),]
controlSample <- Z[which(Z[,2] == 0),]
# Get N1 and N0
n1 <- length(treatedSample[,1])
n0 <- length(controlSample[,1])
# First, I want to generate counterfactual outcomes
# for each treated unit.
# T... |
######################################################################################################
###################### Potrzebna biblioteka ######################
######################################################################################################
... | /Tabu Search.R | no_license | RadekKrol/TabuSearch_r | R | false | false | 5,108 | r | ######################################################################################################
###################### Potrzebna biblioteka ######################
######################################################################################################
... |
## Pooled robust design
### V01-pooled fixed sites
### V02-random sites each year: done terrible performance
library(RMark)
nbends<- 81
bend_km<- runif(nbends,1,12)
phi<- 0.8
p<- 0.3
nprim<- 10 # years
nsec<- 4
dens<- 5 # 10 fish per km
N<-rpois(nbends,dens*bend_km)
N
## NO MOVEMENT
loc<- rep(1:nbends,N)
Z<- matrix(0,... | /_analysis/pooled-rd-v02.R | no_license | mcolvin/PSPAP-Reboot | R | false | false | 1,972 | r | ## Pooled robust design
### V01-pooled fixed sites
### V02-random sites each year: done terrible performance
library(RMark)
nbends<- 81
bend_km<- runif(nbends,1,12)
phi<- 0.8
p<- 0.3
nprim<- 10 # years
nsec<- 4
dens<- 5 # 10 fish per km
N<-rpois(nbends,dens*bend_km)
N
## NO MOVEMENT
loc<- rep(1:nbends,N)
Z<- matrix(0,... |
library("PhysicalActivity");
source("functions.R")
source("PhysicalActivity/R/nthOccurance.R")
source("/home/dewoller/mydoc/research/noraShields/students/carlon/stats/func.R")
a=readCountsDataRT3("test.csv")
markingCarlon=markWearing(a)
markingStandard=wearingMarking(a,
perMinuteCts=1
... | /load.R | no_license | dewoller/foot_health_2015 | R | false | false | 373 | r | library("PhysicalActivity");
source("functions.R")
source("PhysicalActivity/R/nthOccurance.R")
source("/home/dewoller/mydoc/research/noraShields/students/carlon/stats/func.R")
a=readCountsDataRT3("test.csv")
markingCarlon=markWearing(a)
markingStandard=wearingMarking(a,
perMinuteCts=1
... |
#' @title
#' Mode -- most frequent value of a variable
#'
#' @description
#' Caclulate and return the most frequently occuring value of a vector.
#'
#' @param x A vector of values
#' @param na.rm a logical value indicating whether `NA` values should be
#' stripped before the computation proceeds.
#'
#' @r... | /R/calc_mode.R | permissive | emilelatour/lamisc | R | false | false | 1,526 | r |
#' @title
#' Mode -- most frequent value of a variable
#'
#' @description
#' Caclulate and return the most frequently occuring value of a vector.
#'
#' @param x A vector of values
#' @param na.rm a logical value indicating whether `NA` values should be
#' stripped before the computation proceeds.
#'
#' @r... |
# This function predicts partition coefficients for all tissues, then lumps them into a single compartment. The effective volume of distribution is calculated by summing each tissues volume times it's partition coefficient relative to plasma. Plasma, and the paritioning into RBCs are also added to get the total volume ... | /R/Calc_volume_of_distribution.R | no_license | HQData/CompTox-ExpoCast-httk | R | false | false | 7,671 | r | # This function predicts partition coefficients for all tissues, then lumps them into a single compartment. The effective volume of distribution is calculated by summing each tissues volume times it's partition coefficient relative to plasma. Plasma, and the paritioning into RBCs are also added to get the total volume ... |
# library(data.table)
# library(Rtsne)
# library(tsne)
# rm(list = ls()); gc()
# load(file = "./modelData/feat_all_extra_imputed_cleaned_pca_0527.RData")
#
# predictors =colnames(fnl.dat)[!colnames(fnl.dat) %in% c('Patient_ID','response')]
# setDF(fnl.dat)
# fnl.dat = as.matrix(fnl.dat[, predictors])
#
# set.seed(8) ... | /tsne.R | no_license | ivanliu1989/datathon2017 | R | false | false | 3,369 | r | # library(data.table)
# library(Rtsne)
# library(tsne)
# rm(list = ls()); gc()
# load(file = "./modelData/feat_all_extra_imputed_cleaned_pca_0527.RData")
#
# predictors =colnames(fnl.dat)[!colnames(fnl.dat) %in% c('Patient_ID','response')]
# setDF(fnl.dat)
# fnl.dat = as.matrix(fnl.dat[, predictors])
#
# set.seed(8) ... |
# Libraries loaded
library(dplyr)
library(tm)
library(ggplot2)
library(RWeka)
library(stringi)
library(knitr)
library(slam)
# Data file and connections established
con <- file('en_US.blogs.txt', 'r')
blogsdata <- readLines(con, skipNul = TRUE)
close(con)
con <- file('en_US.news.txt', 'r')
newsdat... | /ngrams.R | no_license | generalinsight/CourseraDataScienceCapstone | R | false | false | 2,843 | r |
# Libraries loaded
library(dplyr)
library(tm)
library(ggplot2)
library(RWeka)
library(stringi)
library(knitr)
library(slam)
# Data file and connections established
con <- file('en_US.blogs.txt', 'r')
blogsdata <- readLines(con, skipNul = TRUE)
close(con)
con <- file('en_US.news.txt', 'r')
newsdat... |
% Generated by roxygen2 (4.0.2): do not edit by hand
\name{deployToShinyApps}
\alias{deployToShinyApps}
\title{Deploy VDB to shinyapps.io}
\usage{
deployToShinyApps(vdbConn = getOption("vdbConn"), appName = NULL,
account = NULL, redeploy = TRUE, size = NULL, instances = NULL,
quiet = FALSE)
}
\arguments{
\item{vdbC... | /Analyze/man/deployToShinyApps.Rd | permissive | alacer/renaissance | R | false | false | 1,091 | rd | % Generated by roxygen2 (4.0.2): do not edit by hand
\name{deployToShinyApps}
\alias{deployToShinyApps}
\title{Deploy VDB to shinyapps.io}
\usage{
deployToShinyApps(vdbConn = getOption("vdbConn"), appName = NULL,
account = NULL, redeploy = TRUE, size = NULL, instances = NULL,
quiet = FALSE)
}
\arguments{
\item{vdbC... |
% Generated by roxygen2 (4.0.1): do not edit by hand
\name{run.ensemble.analysis}
\alias{run.ensemble.analysis}
\title{run ensemble.analysis}
\usage{
run.ensemble.analysis(plot.timeseries = NA)
}
\arguments{
\item{plot.timeseries}{if TRUE plots a modeled timeseries of target variable(s) with CIs}
}
\value{
nothing, cre... | /modules/uncertainty/man/run.ensemble.analysis.Rd | permissive | gbromley/pecan | R | false | false | 445 | rd | % Generated by roxygen2 (4.0.1): do not edit by hand
\name{run.ensemble.analysis}
\alias{run.ensemble.analysis}
\title{run ensemble.analysis}
\usage{
run.ensemble.analysis(plot.timeseries = NA)
}
\arguments{
\item{plot.timeseries}{if TRUE plots a modeled timeseries of target variable(s) with CIs}
}
\value{
nothing, cre... |
## I'm using R version 3.5.1 right now
## Contains code necessary to generate simulated datasets considered
## Code was adapted for non-parallel computation and streamlined for H1 midVagina Template
## Source code from https://users.ugent.be/~shawinke/ABrokenPromise/02_dataGeneration.html
################... | /RCode/DataGeneration.R | no_license | matthewlouisdavisBioStat/Rank-Normalization-Empowers-a-T-Test | R | false | false | 34,689 | r |
## I'm using R version 3.5.1 right now
## Contains code necessary to generate simulated datasets considered
## Code was adapted for non-parallel computation and streamlined for H1 midVagina Template
## Source code from https://users.ugent.be/~shawinke/ABrokenPromise/02_dataGeneration.html
################... |
#' Collect additional citations from the supplied edge list.
#'
#' `edge_list_expansion` insert the edge list from the results of `generateEdgeList`
#' @details
#' `edge_list` must come from the result of generateEdgeList
#'
#' @param edge_list edge_list results, as obtained from `generateEdgeList` (see details)
#' @r... | /R/edge_list_expansion.R | no_license | gdancik/pmc2nc | R | false | false | 1,197 | r | #' Collect additional citations from the supplied edge list.
#'
#' `edge_list_expansion` insert the edge list from the results of `generateEdgeList`
#' @details
#' `edge_list` must come from the result of generateEdgeList
#'
#' @param edge_list edge_list results, as obtained from `generateEdgeList` (see details)
#' @r... |
# Testing other features
library(RLT)
set.seed(1)
trainn = 1000
testn = 500
n = trainn + testn
p = 30
X1 = matrix(rnorm(n*p/2), n, p/2)
X2 = matrix(as.integer(runif(n*p/2)*3), n, p/2)
X = data.frame(X1, X2)
for (j in (p/2 + 1):p) X[,j] = as.factor(X[,j])
y = 1 + X[, 1] + rnorm(n)
trainX = X[1:trainn, ]
trainY = y... | /test_other.r | no_license | hwzhousite/RLT | R | false | false | 1,285 | r | # Testing other features
library(RLT)
set.seed(1)
trainn = 1000
testn = 500
n = trainn + testn
p = 30
X1 = matrix(rnorm(n*p/2), n, p/2)
X2 = matrix(as.integer(runif(n*p/2)*3), n, p/2)
X = data.frame(X1, X2)
for (j in (p/2 + 1):p) X[,j] = as.factor(X[,j])
y = 1 + X[, 1] + rnorm(n)
trainX = X[1:trainn, ]
trainY = y... |
### Create data for use with DR simulation code.
# This script takes data from DHS 2007 & 2013 and MICS 2014 and combines them
# into a single data set. In addition we create as raster file with rural and
# urban distinctions as pulled from the 2010 census.
.libPaths(c("~/R3.6/", .libPaths()))
rm(list=ls())
set.seed(1... | /data-raw/data_clean.R | no_license | nmmarquez/DRU5MR | R | false | false | 13,851 | r | ### Create data for use with DR simulation code.
# This script takes data from DHS 2007 & 2013 and MICS 2014 and combines them
# into a single data set. In addition we create as raster file with rural and
# urban distinctions as pulled from the 2010 census.
.libPaths(c("~/R3.6/", .libPaths()))
rm(list=ls())
set.seed(1... |
# some examples about dplyr
# about filter
library(dplyr)
Name = c("zhang3", "li4", "wang5", "zhao6")
sID = c(1, 2, 3, 4)
Stat = c(60, 70, 90, 90)
Form = data.frame(Name, sID, Stat)
filter(Form, Stat == 90)
# about arrange
library(dplyr)
Name = c("zhang3", "li4", "wang5", "zhao6")
sID = c(1, 2, 3, 4)
Stat = c(100, 70... | /ran-you 2017310812 statistics17 L3.R | no_license | ran-you/homework-of-statcomp | R | false | false | 1,656 | r | # some examples about dplyr
# about filter
library(dplyr)
Name = c("zhang3", "li4", "wang5", "zhao6")
sID = c(1, 2, 3, 4)
Stat = c(60, 70, 90, 90)
Form = data.frame(Name, sID, Stat)
filter(Form, Stat == 90)
# about arrange
library(dplyr)
Name = c("zhang3", "li4", "wang5", "zhao6")
sID = c(1, 2, 3, 4)
Stat = c(100, 70... |
test_that("dataone library loads", {
expect_true(require(dataone))
})
test_that("D1Client constructors", {
skip_on_cran()
library(dataone)
#cli <- new("D1Client")
expect_false(is.null(d1cProd))
expect_match(class(d1cProd), "D1Client")
expect_match(d1cProd@cn@baseURL, "https://... | /tests/testthat/test.D1Client.R | permissive | DataONEorg/rdataone | R | false | false | 32,509 | r | test_that("dataone library loads", {
expect_true(require(dataone))
})
test_that("D1Client constructors", {
skip_on_cran()
library(dataone)
#cli <- new("D1Client")
expect_false(is.null(d1cProd))
expect_match(class(d1cProd), "D1Client")
expect_match(d1cProd@cn@baseURL, "https://... |
context("test-fitgllvm")
test_that("basic data fitting works", {
data(microbialdata)
X <- microbialdata$Xenv[1:30,]
y <- microbialdata$Y[1:30, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:35]]
f0<-gllvm(y, family = poisson(), seed = 999)
f1<-gllvm(y, family = "negative.binomial", seed = 999)
... | /tests/testthat/test-fitgllvm.R | no_license | Raykova/gllvm | R | false | false | 2,283 | r | context("test-fitgllvm")
test_that("basic data fitting works", {
data(microbialdata)
X <- microbialdata$Xenv[1:30,]
y <- microbialdata$Y[1:30, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:35]]
f0<-gllvm(y, family = poisson(), seed = 999)
f1<-gllvm(y, family = "negative.binomial", seed = 999)
... |
## code for the pie chart
library("plotrix") #get the library
x<-c(10,5,100,4) #create population data in Lakh for the length
lbl<-c("Raipur","Bilaspur","Delhi","Goa")
perc<-round(100*x/sum(x),1) # % for all city
png(file="2Dpiepercentage.png") #give the file name
pie(x,lbl=... | /d object.R | no_license | AMITPKR/R_chart-graphics | R | false | false | 500 | r | ## code for the pie chart
library("plotrix") #get the library
x<-c(10,5,100,4) #create population data in Lakh for the length
lbl<-c("Raipur","Bilaspur","Delhi","Goa")
perc<-round(100*x/sum(x),1) # % for all city
png(file="2Dpiepercentage.png") #give the file name
pie(x,lbl=... |
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/ResampleDesc.R
\name{makeResampleDesc}
\alias{ResampleDesc}
\alias{makeResampleDesc}
\title{Create a description object for a resampling strategy.}
\usage{
makeResampleDesc(method, predict = "test", ..., stratify = FALSE,
stratify.c... | /man/makeResampleDesc.Rd | no_license | dickoa/mlr | R | false | false | 4,319 | rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/ResampleDesc.R
\name{makeResampleDesc}
\alias{ResampleDesc}
\alias{makeResampleDesc}
\title{Create a description object for a resampling strategy.}
\usage{
makeResampleDesc(method, predict = "test", ..., stratify = FALSE,
stratify.c... |
n_biostrat=62
biostrat=1:62
# for biostrat data, or Taxa FADs,LADs, the biostrat variable is the numbers of the columns with taxa
n_pmag=1
pmag=63
# pmag is a list of the column(s) with paleomagnetic signals, or really any binary data, NA values are not counted
n_dates=3
dates=matrix(c(64,0,65,0,1000,65,0,66,0,1000,... | /attachment_2 (2) (1)/penalty_spec_template.R | no_license | 97joseph/R_to_C-Code-Conversion | R | false | false | 1,220 | r | n_biostrat=62
biostrat=1:62
# for biostrat data, or Taxa FADs,LADs, the biostrat variable is the numbers of the columns with taxa
n_pmag=1
pmag=63
# pmag is a list of the column(s) with paleomagnetic signals, or really any binary data, NA values are not counted
n_dates=3
dates=matrix(c(64,0,65,0,1000,65,0,66,0,1000,... |
######################### TIM
subtree <- function(object,C)
UseMethod("subtree")
prune <- function(object,v=5,sd.mult=0.5,plot=TRUE)
UseMethod("prune")
get.w <- function(object,C)
UseMethod("get.w")
get.t <- function(object,C)
UseMethod("get.t")
thresh <- function(object,data,C,postmed=TRUE)
UseMethod("t... | /treethresh/R/treethresh.R | no_license | ingted/R-Examples | R | false | false | 18,516 | r | ######################### TIM
subtree <- function(object,C)
UseMethod("subtree")
prune <- function(object,v=5,sd.mult=0.5,plot=TRUE)
UseMethod("prune")
get.w <- function(object,C)
UseMethod("get.w")
get.t <- function(object,C)
UseMethod("get.t")
thresh <- function(object,data,C,postmed=TRUE)
UseMethod("t... |
\name{EWBurials}
\alias{EWBurials}
\docType{data}
\title{
Ernest Witte Cemetery, Austin, County, Texas, U.S.A.
}
\description{
Sex, age, burial group, location, and burial orientation and direction facing from the Ernest Witte site, a Late Archaic cemetery in Texas (Hall 1981).
}
\usage{data(EWBurials)}
\format{
A d... | /man/EWBurials.Rd | no_license | cran/archdata | R | false | false | 2,635 | rd | \name{EWBurials}
\alias{EWBurials}
\docType{data}
\title{
Ernest Witte Cemetery, Austin, County, Texas, U.S.A.
}
\description{
Sex, age, burial group, location, and burial orientation and direction facing from the Ernest Witte site, a Late Archaic cemetery in Texas (Hall 1981).
}
\usage{data(EWBurials)}
\format{
A d... |
source("Bootstrapping (1).r")
source("EnergyOptim.r")
load("DCG.RData")
load("CoupGeo.RData")
###
iter=500
Energy.coarse=numeric(iter)
Energy.fine=numeric(iter)
for (l in 1:iter){
sub1=Bootbinary(reptl[1:11,1:6])$Matrix
sub2=Bootbinary(reptl[1:11,7:44])$Matrix
sub3=Bootbinary(reptl[12:20,1:6])$Matrix
sub... | /code/reptl.r | no_license | guanjiahui/nested_bipartite_network | R | false | false | 2,648 | r | source("Bootstrapping (1).r")
source("EnergyOptim.r")
load("DCG.RData")
load("CoupGeo.RData")
###
iter=500
Energy.coarse=numeric(iter)
Energy.fine=numeric(iter)
for (l in 1:iter){
sub1=Bootbinary(reptl[1:11,1:6])$Matrix
sub2=Bootbinary(reptl[1:11,7:44])$Matrix
sub3=Bootbinary(reptl[12:20,1:6])$Matrix
sub... |
X_test <- read.table("./getdata_projectfiles_UCI HAR Dataset/UCI HAR Dataset/test/X_test.txt", quote="\"", comment.char="")
y_test <- read.table("./getdata_projectfiles_UCI HAR Dataset/UCI HAR Dataset/test/y_test.txt", quote="\"", comment.char="")
subject_test <- read.table("./getdata_projectfiles_UCI HAR Dataset/UCI H... | /run_analysis.R | no_license | mbestry/tidy_dataset_assignment | R | false | false | 2,450 | r | X_test <- read.table("./getdata_projectfiles_UCI HAR Dataset/UCI HAR Dataset/test/X_test.txt", quote="\"", comment.char="")
y_test <- read.table("./getdata_projectfiles_UCI HAR Dataset/UCI HAR Dataset/test/y_test.txt", quote="\"", comment.char="")
subject_test <- read.table("./getdata_projectfiles_UCI HAR Dataset/UCI H... |
##### 根据导师在3月初给的资料做划分区间进行分析 ###
##### 分析波动性
##### 分析横向的波动性
##### 预处理 ########
library(readxl)
library(tidyr)
library(dplyr)
library(urca)
library(lmtest)
library(xlsx)
library(dyn)
root_path <- getwd()
data_path <- "/Users/ethan/Documents/Ethan/CoreFiles/CodesFile/MoneyMismatch/data"
setwd(root_path)
source(past... | /codes/R programs/MoneyMismatch/volatility_compare_201903.R | no_license | EthanSystem/MoneyMismatch | R | false | false | 34,400 | r |
##### 根据导师在3月初给的资料做划分区间进行分析 ###
##### 分析波动性
##### 分析横向的波动性
##### 预处理 ########
library(readxl)
library(tidyr)
library(dplyr)
library(urca)
library(lmtest)
library(xlsx)
library(dyn)
root_path <- getwd()
data_path <- "/Users/ethan/Documents/Ethan/CoreFiles/CodesFile/MoneyMismatch/data"
setwd(root_path)
source(past... |
# This is the R_PROFILE.R file
# This file is executed before teh code in the 'R' subdirectory
# This file should not be used.
| /R/R_PROFILE.R | no_license | jestill/gencart | R | false | false | 127 | r | # This is the R_PROFILE.R file
# This file is executed before teh code in the 'R' subdirectory
# This file should not be used.
|
#' @title Plot Isoform Expression Data
#' @description Visualize isoform expression data for exploratory data analysis.
#'
#' @details
#' The \code{isoPlot} is designed to make visualization of isoform expression data simple and easy for R novices and bioinformaticians alike.
#' The function is an S3 generic that accep... | /R/isoPlot.R | no_license | crisjs/bvt | R | false | false | 16,466 | r | #' @title Plot Isoform Expression Data
#' @description Visualize isoform expression data for exploratory data analysis.
#'
#' @details
#' The \code{isoPlot} is designed to make visualization of isoform expression data simple and easy for R novices and bioinformaticians alike.
#' The function is an S3 generic that accep... |
#load libraries
library(quantreg)
library(glmnet)
library(magrittr)
library(purrr)
library(msaenet)
#load data
#data.half <- readRDS()
#full.data <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertation/fulldata_091620.RData")
#half.data <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertat... | /Model_Application/Testing/MSAdaELNet5_single_testing.R | no_license | multach87/Dissertation | R | false | false | 10,055 | r | #load libraries
library(quantreg)
library(glmnet)
library(magrittr)
library(purrr)
library(msaenet)
#load data
#data.half <- readRDS()
#full.data <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertation/fulldata_091620.RData")
#half.data <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertat... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CST_RFSlope.R
\name{CST_RFSlope}
\alias{CST_RFSlope}
\title{RainFARM spectral slopes from a CSTools object}
\usage{
CST_RFSlope(data, kmin = 1, time_dim = NULL, ncores = NULL)
}
\arguments{
\item{data}{An object of the class 's2dv_cube', cont... | /man/CST_RFSlope.Rd | no_license | cran/CSTools | R | false | true | 2,212 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CST_RFSlope.R
\name{CST_RFSlope}
\alias{CST_RFSlope}
\title{RainFARM spectral slopes from a CSTools object}
\usage{
CST_RFSlope(data, kmin = 1, time_dim = NULL, ncores = NULL)
}
\arguments{
\item{data}{An object of the class 's2dv_cube', cont... |
\name{hmap.annotate}
\alias{hmap.annotate}
\title{
Add a row and column annotations to a plot-region based heatmap built with 'hmap'
}
\description{
Annotation of rows or columns in a 'hmap'-plot. By default, rectangles aligned with either rows or columns are plotted to the right-side or lower-side of the heatmap... | /man/hmap.annotate.Rd | no_license | cran/hamlet | R | false | false | 4,573 | rd | \name{hmap.annotate}
\alias{hmap.annotate}
\title{
Add a row and column annotations to a plot-region based heatmap built with 'hmap'
}
\description{
Annotation of rows or columns in a 'hmap'-plot. By default, rectangles aligned with either rows or columns are plotted to the right-side or lower-side of the heatmap... |
# Load data
cc = fread('entityTypeGrouping.csv')
entity.region = fread('data/EntitiesByRegion.csv')
entity.region[, asOfDate:= as.Date(asOfDate)]
entity.ofc = fread('data/EntitiesByOFC.csv')
entity.ofc[, asOfDate:= as.Date(asOfDate)]
link.node.ratio = fread('data/linkNodeRatio.csv')
link.node.ratio[, asOfDate:= as.Date... | /app/_loadData.R | no_license | nemochina2008/nic-structure | R | false | false | 599 | r | # Load data
cc = fread('entityTypeGrouping.csv')
entity.region = fread('data/EntitiesByRegion.csv')
entity.region[, asOfDate:= as.Date(asOfDate)]
entity.ofc = fread('data/EntitiesByOFC.csv')
entity.ofc[, asOfDate:= as.Date(asOfDate)]
link.node.ratio = fread('data/linkNodeRatio.csv')
link.node.ratio[, asOfDate:= as.Date... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/anova_psem.R
\name{anovaTable}
\alias{anovaTable}
\title{Single anova}
\usage{
anovaTable(object, anovafun = "Anova", digits = 3)
}
\description{
Single anova
}
\keyword{internal}
| /man/anovaTable.Rd | no_license | jslefche/piecewiseSEM | R | false | true | 258 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/anova_psem.R
\name{anovaTable}
\alias{anovaTable}
\title{Single anova}
\usage{
anovaTable(object, anovafun = "Anova", digits = 3)
}
\description{
Single anova
}
\keyword{internal}
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/nlaRiparianVegetation.r
\name{nlaRiparianVegetation}
\alias{nlaRiparianVegetation}
\title{Calculate NLA Riparian Zone and Vegetation Metrics}
\usage{
nlaRiparianVegetation(bigTrees = NULL, bigTrees_dd = NULL,
smallTrees = NULL, smallTrees_d... | /man/nlaRiparianVegetation.Rd | no_license | jasonelaw/aquamet | R | false | true | 16,518 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/nlaRiparianVegetation.r
\name{nlaRiparianVegetation}
\alias{nlaRiparianVegetation}
\title{Calculate NLA Riparian Zone and Vegetation Metrics}
\usage{
nlaRiparianVegetation(bigTrees = NULL, bigTrees_dd = NULL,
smallTrees = NULL, smallTrees_d... |
# Análisis del marco de datos sobre los Estados de USA.
library(tidyverse)
library(maps)
library(mapproj)
library(ggplot2)
source("data/helpers.R")
states <- readRDS("data/counties.rds")
head(states)
colnames(states) <- c("name", "total.pop", "Human", "Elf", "Orc", "Wizard")
head(states)
var <- states... | /ShinyBeginnings/09-StatesDataAnalysis.R | no_license | Angnar1997/ShinyPath | R | false | false | 462 | r | # Análisis del marco de datos sobre los Estados de USA.
library(tidyverse)
library(maps)
library(mapproj)
library(ggplot2)
source("data/helpers.R")
states <- readRDS("data/counties.rds")
head(states)
colnames(states) <- c("name", "total.pop", "Human", "Elf", "Orc", "Wizard")
head(states)
var <- states... |
library(shiny)
library(tidyverse)
library(shinythemes)
library(here)
library(plotly)
library(shinydashboard)
load("DBdata[asmt][v4.491].RData")
#Tidy format: tb.data --- Total biomass data
#No data: ATBTUNAEATL, ATBTUNAWATL (both ADDED as all NAs!)
tuna_biomass <- tb.data %>%
select(ALBANATL, ALBASATL, BIGEYEATL... | /app.R | no_license | CaitieReza/mpa_app | R | false | false | 42,597 | r | library(shiny)
library(tidyverse)
library(shinythemes)
library(here)
library(plotly)
library(shinydashboard)
load("DBdata[asmt][v4.491].RData")
#Tidy format: tb.data --- Total biomass data
#No data: ATBTUNAEATL, ATBTUNAWATL (both ADDED as all NAs!)
tuna_biomass <- tb.data %>%
select(ALBANATL, ALBASATL, BIGEYEATL... |
#' Fix name out
#'
#' Function to fix the names when subsetting
#'
#' @importFrom methods as
#' @param nc_out a character string
#' @return No return value, called to rename subsetted file
#' @keywords internal
fix_name_out <- function(nc_out){
dummie_name <- name_check(nc_out)
dummie_date <- show_info(nc_out)
... | /R/fix_name_out.R | no_license | imarkonis/pRecipe | R | false | false | 1,836 | r | #' Fix name out
#'
#' Function to fix the names when subsetting
#'
#' @importFrom methods as
#' @param nc_out a character string
#' @return No return value, called to rename subsetted file
#' @keywords internal
fix_name_out <- function(nc_out){
dummie_name <- name_check(nc_out)
dummie_date <- show_info(nc_out)
... |
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