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 |
|---|---|---|---|---|---|---|---|---|---|
###### Plotting Original Curves ######
# Packages
library(data.table)
library(ggplot2)
# Auxiliary functions
source("R/aux_functions.R")
# Function to evaluate function points; adds points evaluated in the beggining and ending of the interval
points_of_original_function = function(address_hash, dt){
dt = dt[addr... | /plot_original_curves.R | no_license | brendaprallon/ripple-FDA | R | false | false | 2,542 | r | ###### Plotting Original Curves ######
# Packages
library(data.table)
library(ggplot2)
# Auxiliary functions
source("R/aux_functions.R")
# Function to evaluate function points; adds points evaluated in the beggining and ending of the interval
points_of_original_function = function(address_hash, dt){
dt = dt[addr... |
#' Generate Polygons from Isobaths
#'
#' From an input bathymetry and chosen depths, turns areas between isobaths into polygons.
#' An input polygon may optionally be given to constrain boundaries.
#' The accuracy is dependent on the resolution of the bathymetry raster
#' (see \code{\link{load_Bathy}} to get high resol... | /R/get_iso_polys.R | no_license | ccamlr/CCAMLRGIS | R | false | false | 3,393 | r | #' Generate Polygons from Isobaths
#'
#' From an input bathymetry and chosen depths, turns areas between isobaths into polygons.
#' An input polygon may optionally be given to constrain boundaries.
#' The accuracy is dependent on the resolution of the bathymetry raster
#' (see \code{\link{load_Bathy}} to get high resol... |
fig_path_sav = "C:\\Users\\orlov\\Desktop\\figures_sapovirus\\"
fig_path_nov = "C:\\Users\\orlov\\Desktop\\figures_norovirus\\"
sav = read.dna(as.character("C:\\Users\\orlov\\Documents\\term_project\\alignments\\sapovirus_genomes_full_aln_100gp_0.5_genotyped.fasta"), format="fasta", as.character=TRUE)
nov = read.dna... | /make_pairwise_dist.r | no_license | orlovartem/pairwise_distances | R | false | false | 3,830 | r | fig_path_sav = "C:\\Users\\orlov\\Desktop\\figures_sapovirus\\"
fig_path_nov = "C:\\Users\\orlov\\Desktop\\figures_norovirus\\"
sav = read.dna(as.character("C:\\Users\\orlov\\Documents\\term_project\\alignments\\sapovirus_genomes_full_aln_100gp_0.5_genotyped.fasta"), format="fasta", as.character=TRUE)
nov = read.dna... |
test_rep_reportQualityCheckRawData <- function() {
normalData <- replicate(8, rnorm(n=3000, mean=11.5, sd=2.2))
normalData <- 2^normalData
## Test
reportQualityCheckRawData(
normalData,
file.path(getwd(), 'temp'),
stdout(), #file.path(getwd(), 'temp', 'out_test_rep_r... | /inst/unitTests/test_qck_raw_data.R | no_license | rmylonas/Prots4Prots | R | false | false | 386 | r |
test_rep_reportQualityCheckRawData <- function() {
normalData <- replicate(8, rnorm(n=3000, mean=11.5, sd=2.2))
normalData <- 2^normalData
## Test
reportQualityCheckRawData(
normalData,
file.path(getwd(), 'temp'),
stdout(), #file.path(getwd(), 'temp', 'out_test_rep_r... |
# ****************************************************************
# GOAL : Normalize with various methods:
# - Quantile normalization
# USAGE :
# ****************************************************************
################ load libraries ###############
suppressPackageStartupMessages(library("argparse"))
... | /scripts/R_normalize_data.R | no_license | gauravj49/BulkRnaseqDE | R | false | false | 12,138 | r | # ****************************************************************
# GOAL : Normalize with various methods:
# - Quantile normalization
# USAGE :
# ****************************************************************
################ load libraries ###############
suppressPackageStartupMessages(library("argparse"))
... |
#####################################################################
######## GETTING AND CLEANING DATA ###############################
### ASSIGNMENT NO. 1
## The objective of this analysis is to make the raw data tidy enough for further analysis.
############################################################... | /run_analysis.R | no_license | filmonghere/Getting_And_Cleaning_Data_Ass | R | false | false | 7,596 | r |
#####################################################################
######## GETTING AND CLEANING DATA ###############################
### ASSIGNMENT NO. 1
## The objective of this analysis is to make the raw data tidy enough for further analysis.
############################################################... |
## ----load-libraries------------------------------------------------------
# Load packages required for entire script
library(lubridate) #work with dates
#set working directory to ensure R can find the file we wish to import
#setwd("working-dir-path-here")
#Load csv file of 15 min meterological data from Harvard F... | /TS02-Convert-to-Date-Time-Class-POSIX.R | no_license | mguarinello/NEON-R-Tabular-Time-Series | R | false | false | 3,251 | r | ## ----load-libraries------------------------------------------------------
# Load packages required for entire script
library(lubridate) #work with dates
#set working directory to ensure R can find the file we wish to import
#setwd("working-dir-path-here")
#Load csv file of 15 min meterological data from Harvard F... |
geigen <- function(Amat, Bmat, Cmat)
{
# solve the generalized eigenanalysis problem
#
# max {tr L'AM / sqrt[tr L'BL tr M'CM] w.r.t. L and M
#
# Arguments:
# AMAT ... p by q matrix
# BMAT ... order p symmetric positive definite matrix
# CMAT ... order q symmetric positive definite matri... | /R/geigen.R | no_license | bonniewan/fda | R | false | false | 1,512 | r | geigen <- function(Amat, Bmat, Cmat)
{
# solve the generalized eigenanalysis problem
#
# max {tr L'AM / sqrt[tr L'BL tr M'CM] w.r.t. L and M
#
# Arguments:
# AMAT ... p by q matrix
# BMAT ... order p symmetric positive definite matrix
# CMAT ... order q symmetric positive definite matri... |
c DCNF-Autarky [version 0.0.1].
c Copyright (c) 2018-2019 Swansea University.
c
c Input Clause Count: 7494
c Performing E1-Autarky iteration.
c Remaining clauses count after E-Reduction: 7494
c
c Input Parameter (command line, file):
c input filename QBFLIB/Miller-Marin/trafficlight-controller/tlc04-uniform-depth... | /code/dcnf-ankit-optimized/Results/QBFLIB-2018/E1/Experiments/Miller-Marin/trafficlight-controller/tlc04-uniform-depth-7/tlc04-uniform-depth-7.R | no_license | arey0pushpa/dcnf-autarky | R | false | false | 677 | r | c DCNF-Autarky [version 0.0.1].
c Copyright (c) 2018-2019 Swansea University.
c
c Input Clause Count: 7494
c Performing E1-Autarky iteration.
c Remaining clauses count after E-Reduction: 7494
c
c Input Parameter (command line, file):
c input filename QBFLIB/Miller-Marin/trafficlight-controller/tlc04-uniform-depth... |
expected_values[[runno]] <- list(lik = c(-12044.25, 24106.5, 24158.09), param = c(6.9114,
5.522, 4.235, 0.0099988, 0.19252), stdev_param = c(0.29486, 0.26095,
0.36142, 0.30731, NA), sigma = c(prop.err = 0.19252), parFixedDf = structure(list(
Estimate = c(lVM = 6.91142325517718, lKM = 5.52204347329164,
lVc = ... | /inst/models/values-1.1.1.3-U029_saem-unix.R | no_license | nlmixrdevelopment/nlmixr.examples | R | false | false | 1,979 | r | expected_values[[runno]] <- list(lik = c(-12044.25, 24106.5, 24158.09), param = c(6.9114,
5.522, 4.235, 0.0099988, 0.19252), stdev_param = c(0.29486, 0.26095,
0.36142, 0.30731, NA), sigma = c(prop.err = 0.19252), parFixedDf = structure(list(
Estimate = c(lVM = 6.91142325517718, lKM = 5.52204347329164,
lVc = ... |
#' @rdname bcbioSingleCell
#' @aliases NULL
#' @exportClass bcbioSingleCell
#' @usage NULL
bcbioSingleCell <- setClass(
Class = "bcbioSingleCell",
contains = "SingleCellExperiment"
)
setOldClass(Classes = c("grouped_df", "tbl_df", "tibble"))
| /R/AllClasses.R | permissive | chitrita/bcbioSingleCell | R | false | false | 253 | r | #' @rdname bcbioSingleCell
#' @aliases NULL
#' @exportClass bcbioSingleCell
#' @usage NULL
bcbioSingleCell <- setClass(
Class = "bcbioSingleCell",
contains = "SingleCellExperiment"
)
setOldClass(Classes = c("grouped_df", "tbl_df", "tibble"))
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/writing-options.R
\name{writing-options}
\alias{writing-options}
\title{Writing data options}
\description{
Writing data options
}
\examples{
\dontrun{
# write to disk
(x <- HttpClient$new(url = "https://httpbin.org"))
f <- tempfile()
res <- ... | /man/writing-options.Rd | permissive | hlapp/crul | R | false | true | 2,071 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/writing-options.R
\name{writing-options}
\alias{writing-options}
\title{Writing data options}
\description{
Writing data options
}
\examples{
\dontrun{
# write to disk
(x <- HttpClient$new(url = "https://httpbin.org"))
f <- tempfile()
res <- ... |
setwd("D:\\Education\\stepupanalytics_Blog\\linear regression")
help(package = "MASS")
install.packages("MASS")
install.packages("ISLR")
library(MASS) #loads dataset from the book MASS
library(ISLR) #dataset by Statistical Learning professors
##Simple Linear Regression
# reading data in R
data(Boston)
... | /linear.R | no_license | mdzishanhussain/Linear-Regression-in-R | R | false | false | 1,732 | r | setwd("D:\\Education\\stepupanalytics_Blog\\linear regression")
help(package = "MASS")
install.packages("MASS")
install.packages("ISLR")
library(MASS) #loads dataset from the book MASS
library(ISLR) #dataset by Statistical Learning professors
##Simple Linear Regression
# reading data in R
data(Boston)
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get.R
\name{get}
\alias{get}
\title{Gets a Synapse entity}
\usage{
get(synid)
}
\arguments{
\item{synid}{Synapse Id of an entity}
}
\value{
Entity
}
\description{
Gets a Synapse entity
}
\examples{
library(synapserprototype)
entity <- get('sy... | /man/get.Rd | no_license | thomasyu888/synapserprototype | R | false | true | 329 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get.R
\name{get}
\alias{get}
\title{Gets a Synapse entity}
\usage{
get(synid)
}
\arguments{
\item{synid}{Synapse Id of an entity}
}
\value{
Entity
}
\description{
Gets a Synapse entity
}
\examples{
library(synapserprototype)
entity <- get('sy... |
#### run this file for the pre-registered (confirmatory) analysis
#### main output are the graphs
rm(list=ls())
library(dplyr)
library(ggplot2)
library(MatchIt)
library(multiwayvcov)
library(plm)
library(lmtest)
library(clubSandwich)
library(moments)
library(doParallel)
set.seed(123456789) #not needed for final versi... | /report/attrition.R | no_license | bjvca/baraza | R | false | false | 18,950 | r | #### run this file for the pre-registered (confirmatory) analysis
#### main output are the graphs
rm(list=ls())
library(dplyr)
library(ggplot2)
library(MatchIt)
library(multiwayvcov)
library(plm)
library(lmtest)
library(clubSandwich)
library(moments)
library(doParallel)
set.seed(123456789) #not needed for final versi... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mark.R
\name{summary.bench_mark}
\alias{summary.bench_mark}
\title{Summarize \link[bench:mark]{bench::mark} results.}
\usage{
\method{summary}{bench_mark}(object, filter_gc = TRUE, relative = FALSE, time_unit = NULL, ...)
}
\arguments{
\item{... | /man/summary.bench_mark.Rd | permissive | isabella232/bench-3 | R | false | true | 3,794 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mark.R
\name{summary.bench_mark}
\alias{summary.bench_mark}
\title{Summarize \link[bench:mark]{bench::mark} results.}
\usage{
\method{summary}{bench_mark}(object, filter_gc = TRUE, relative = FALSE, time_unit = NULL, ...)
}
\arguments{
\item{... |
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
library(PointFore)
## -------------------------------------------------------------------------... | /doc/Tutorial.R | no_license | Schmidtpk/PointFore | R | false | false | 4,014 | r | ## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
library(PointFore)
## -------------------------------------------------------------------------... |
library(TrenaProjectMouseMacrophage)
library(RUnit)
#------------------------------------------------------------------------------------------------------------------------
if(!exists("tProj")) {
message(sprintf("--- creating instance of TrenaProjectMouseMacrophage"))
tProj <- TrenaProjectMouseMacrophage();
}... | /inst/unitTests/test_TrenaProjectMouseMacrophage.R | permissive | PriceLab/TrenaProjectMouseMacrophage | R | false | false | 4,520 | r | library(TrenaProjectMouseMacrophage)
library(RUnit)
#------------------------------------------------------------------------------------------------------------------------
if(!exists("tProj")) {
message(sprintf("--- creating instance of TrenaProjectMouseMacrophage"))
tProj <- TrenaProjectMouseMacrophage();
}... |
context("Adding nodes and/or edges from a table to a graph")
test_that("adding nodes from a table to a graph is possible", {
library(tibble)
# Create a data frame for graph nodes
node_table <-
tibble::tribble(
~iso_4217_code, ~curr_number, ~exponent,
"AED", 784, 2,
"AFN", 971, 2,
... | /tests/testthat/test-add_nodes_edges_from_table.R | no_license | DataXujing/DiagrammeR | R | false | false | 20,021 | r | context("Adding nodes and/or edges from a table to a graph")
test_that("adding nodes from a table to a graph is possible", {
library(tibble)
# Create a data frame for graph nodes
node_table <-
tibble::tribble(
~iso_4217_code, ~curr_number, ~exponent,
"AED", 784, 2,
"AFN", 971, 2,
... |
# 提交成功显示
observeEvent(input$submit_oplsda, {
if (input$submit_oplsda>0) {
sendSweetAlert(
session = session,
title = "提交成功!",
text = "数据上传成功，参数设置正确",
type = "success")
}
})
# 导入数据
user_data_oplsda <- reactive({
table_in_test <- read.csv(input$data_input_oplsda$datapath,
... | /main/oplsda_server.R | no_license | lixiang117423/Tools4You | R | false | false | 11,269 | r | # 提交成功显示
observeEvent(input$submit_oplsda, {
if (input$submit_oplsda>0) {
sendSweetAlert(
session = session,
title = "提交成功!",
text = "数据上传成功，参数设置正确",
type = "success")
}
})
# 导入数据
user_data_oplsda <- reactive({
table_in_test <- read.csv(input$data_input_oplsda$datapath,
... |
t=seq(0,2*pi,0.1)
y=sin(t)
plot(t,y,type="l", xlab="time", ylab="Sine wave", main="Graphe de la fonction sinus")
plot(dnorm,-4,4)
#abline(v=0.2)
#abline(v=3)
abline(h=0)
#segments(x0=c(-2), y0=c(0.0), x1=c(3), y1=c(0.3),col="pink")
#segments(x0=c(-2), y0=c(0.0), x1=c(3), y1=c(0.5),col="red")
#segments(x0=c(-2), y0=c(0... | /semestre2/OutilsDonnees/TP2.R | no_license | bistendope/Cours_M1 | R | false | false | 1,331 | r | t=seq(0,2*pi,0.1)
y=sin(t)
plot(t,y,type="l", xlab="time", ylab="Sine wave", main="Graphe de la fonction sinus")
plot(dnorm,-4,4)
#abline(v=0.2)
#abline(v=3)
abline(h=0)
#segments(x0=c(-2), y0=c(0.0), x1=c(3), y1=c(0.3),col="pink")
#segments(x0=c(-2), y0=c(0.0), x1=c(3), y1=c(0.5),col="red")
#segments(x0=c(-2), y0=c(0... |
# server.R
library(tuneR)
library(seewave)
library(dplyr)
library(stringr)
library(tidyr)
library(ggplot2)
library(gridExtra)
source("functions.R")
shinyServer(
function(input, output, session) {
###############
## Defaults
###############
## First look for defaults
if(fil... | /server.R | no_license | steffilazerte/song-extract | R | false | false | 25,237 | r | # server.R
library(tuneR)
library(seewave)
library(dplyr)
library(stringr)
library(tidyr)
library(ggplot2)
library(gridExtra)
source("functions.R")
shinyServer(
function(input, output, session) {
###############
## Defaults
###############
## First look for defaults
if(fil... |
#----Data Frame----
#We can create a dataframe by combining variables of same length.
# Create a, b, c, d variables
a <- c(10,20,30,40)
b <- c('book', 'pen', 'textbook', 'pencil_case')
c <- c(TRUE,FALSE,TRUE,FALSE)
d <- c(2.5, 8, 10, 7)
# Join the variables to create a data frame
df <- data.frame(a,b,c,d)
df
... | /3 DataFrame-DataStructuresinR.R | no_license | rajanimishra128/Data-Analytics | R | false | false | 1,815 | r | #----Data Frame----
#We can create a dataframe by combining variables of same length.
# Create a, b, c, d variables
a <- c(10,20,30,40)
b <- c('book', 'pen', 'textbook', 'pencil_case')
c <- c(TRUE,FALSE,TRUE,FALSE)
d <- c(2.5, 8, 10, 7)
# Join the variables to create a data frame
df <- data.frame(a,b,c,d)
df
... |
RetrieveTWCoBaseURL <- function(API.Location, API) {
# **********************************Header***********************************
# FUNCTION NAME: RetrieveTWCoBaseURL
# DESCRIPTION: This function accepts a data frame in the style of
# modelerDataModel and will return a data frame will legal R field names that
... | /Code/Functions/RetrieveTWCoBaseURL.R | no_license | hangtime79/TWCo_History_On_Demand | R | false | false | 2,188 | r | RetrieveTWCoBaseURL <- function(API.Location, API) {
# **********************************Header***********************************
# FUNCTION NAME: RetrieveTWCoBaseURL
# DESCRIPTION: This function accepts a data frame in the style of
# modelerDataModel and will return a data frame will legal R field names that
... |
# Author: TW
#require(testthat)
context("plotFingerPrint")
if (!exists("Example_DETha98")) load("data/Example_DETha98.RData")
EddyData.F <- Example_DETha98
#Include POSIX time stamp column
EddyDataWithPosix.F <- suppressMessages(fConvertTimeToPosix(
EddyData.F, 'YDH', Year = 'Year', Day = 'DoY', Hour = 'Hour'))
# c... | /tests/testthat/test_plotFingerprint.R | no_license | bgctw/REddyProc | R | false | false | 3,440 | r | # Author: TW
#require(testthat)
context("plotFingerPrint")
if (!exists("Example_DETha98")) load("data/Example_DETha98.RData")
EddyData.F <- Example_DETha98
#Include POSIX time stamp column
EddyDataWithPosix.F <- suppressMessages(fConvertTimeToPosix(
EddyData.F, 'YDH', Year = 'Year', Day = 'DoY', Hour = 'Hour'))
# c... |
test_that("ci", {
skip_if_not_installed("lme4")
model <- lm(mpg ~ wt, data = mtcars)
expect_equal(suppressMessages(ci(model))[1, 3], 33.4505, tolerance = 0.01)
expect_equal(suppressMessages(ci(model, ci = c(0.7, 0.8)))[1, 3], 35.30486, tolerance = 0.01)
model <- glm(vs ~ wt, family = "binomial", data... | /tests/testthat/test-ci.R | no_license | cran/parameters | R | false | false | 2,007 | r | test_that("ci", {
skip_if_not_installed("lme4")
model <- lm(mpg ~ wt, data = mtcars)
expect_equal(suppressMessages(ci(model))[1, 3], 33.4505, tolerance = 0.01)
expect_equal(suppressMessages(ci(model, ci = c(0.7, 0.8)))[1, 3], 35.30486, tolerance = 0.01)
model <- glm(vs ~ wt, family = "binomial", data... |
library(base)
library(utils)
library(data.table)
# The function downloads the Samsung data and extracts it
download.data <- function () {
zip.url <- 'https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip'
zip.file <- 'dataset.zip'
download.file(zip.url,... | /run_analysis.R | no_license | Beassoum/getdata-Project | R | false | false | 3,277 | r | library(base)
library(utils)
library(data.table)
# The function downloads the Samsung data and extracts it
download.data <- function () {
zip.url <- 'https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip'
zip.file <- 'dataset.zip'
download.file(zip.url,... |
# Simple function to generate filename of csv report in desired format
generate_filename <- function(report,date){
# put generated file in a folder called reports in home directory, and generate filename based on name of report and user input
filename <- paste("~/reports/",report,device_name,"_",date,".csv",sep = "... | /reporting/generate_filename.R | no_license | L3Vyt/edulution_scripts | R | false | false | 325 | r | # Simple function to generate filename of csv report in desired format
generate_filename <- function(report,date){
# put generated file in a folder called reports in home directory, and generate filename based on name of report and user input
filename <- paste("~/reports/",report,device_name,"_",date,".csv",sep = "... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GenFactorMatrix.R
\name{GenFactorMatrix}
\alias{GenFactorMatrix}
\title{Generate Factor Loadings Matrix}
\usage{
GenFactorMatrix(nfactors = 5, items = c(5, 5, 5, 5, 5), itemsR = c(2, 2,
2, 2, 2), loading = 0.5, loading_norm = FALSE, loading... | /man/GenFactorMatrix.Rd | no_license | R-Computing-Lab/enumR | R | false | true | 919 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GenFactorMatrix.R
\name{GenFactorMatrix}
\alias{GenFactorMatrix}
\title{Generate Factor Loadings Matrix}
\usage{
GenFactorMatrix(nfactors = 5, items = c(5, 5, 5, 5, 5), itemsR = c(2, 2,
2, 2, 2), loading = 0.5, loading_norm = FALSE, loading... |
N0 <- 10000
lambda <- 1.5
f <- function(t) lambda * exp(-lambda*t)
F <- function(t) 1 - exp(-lambda * t)
inv_F <- function(t) exp(-lambda * t)
reverse_exp_function <- function(x) -1 / lambda * log(x)
sequence <- sort(sapply(runif(N0, 0, 1), reverse_exp_function))
max_t <- max(sequence)
pdf("out.pdf")
N <- sapply(c(... | /8sem/SR/lab3/lab3.R | no_license | azhi/BSUIR_labs | R | false | false | 1,820 | r | N0 <- 10000
lambda <- 1.5
f <- function(t) lambda * exp(-lambda*t)
F <- function(t) 1 - exp(-lambda * t)
inv_F <- function(t) exp(-lambda * t)
reverse_exp_function <- function(x) -1 / lambda * log(x)
sequence <- sort(sapply(runif(N0, 0, 1), reverse_exp_function))
max_t <- max(sequence)
pdf("out.pdf")
N <- sapply(c(... |
## original code was designed to detect segfaults/hangs from error handling
library(lmeAddSigma)
set.seed(101)
d <- expand.grid(block=LETTERS[1:26],rep=1:100)
d$x <- runif(nrow(d))
reff_f <- rnorm(length(levels(d$block)),sd=1)
## need intercept large enough to avoid negative values
d$eta0 <- 4+3*d$x ## version withou... | /tests/throw.R | no_license | naef-lab/lmeAddSigma | R | false | false | 814 | r | ## original code was designed to detect segfaults/hangs from error handling
library(lmeAddSigma)
set.seed(101)
d <- expand.grid(block=LETTERS[1:26],rep=1:100)
d$x <- runif(nrow(d))
reff_f <- rnorm(length(levels(d$block)),sd=1)
## need intercept large enough to avoid negative values
d$eta0 <- 4+3*d$x ## version withou... |
boxplot(sphere10_32particles_cpu_multi_runs$V11, sphere10_32particles_gpu_multi_runs$V11, names=c("CPU", "GPU"), main="SPHERE(10) - 32 particles - 51 runs", ylab="Fitness value")
boxplot(sphere10_32particles_cpu_time_multi_runs$V1, sphere10_32particles_gpu_time_multi_runs$V1, names=c("CPU", "GPU"), main="SPHERE(10) -... | /scripts/sphere10_32particles_multi_runs.r | no_license | AOE-khkhan/CUDA-final-project | R | false | false | 373 | r |
boxplot(sphere10_32particles_cpu_multi_runs$V11, sphere10_32particles_gpu_multi_runs$V11, names=c("CPU", "GPU"), main="SPHERE(10) - 32 particles - 51 runs", ylab="Fitness value")
boxplot(sphere10_32particles_cpu_time_multi_runs$V1, sphere10_32particles_gpu_time_multi_runs$V1, names=c("CPU", "GPU"), main="SPHERE(10) -... |
# Import libraries
library(readr)
library(ggplot2)
library(dplyr)
library(mvtnorm)
# Parms
n <- 100 # number data points per centroid
sd <- 1 # standard deviation for each centroid
# Define our four centroids
centroid_1 <- c(0, 0)
centroid_2 <- c(10, 10)
centroid_3 <- c(0, 10)
centroid_4 <- c(10, 0)
# Make covarianc... | /KNN_data_script.R | no_license | CME323-isomap/CME-research | R | false | false | 1,147 | r | # Import libraries
library(readr)
library(ggplot2)
library(dplyr)
library(mvtnorm)
# Parms
n <- 100 # number data points per centroid
sd <- 1 # standard deviation for each centroid
# Define our four centroids
centroid_1 <- c(0, 0)
centroid_2 <- c(10, 10)
centroid_3 <- c(0, 10)
centroid_4 <- c(10, 0)
# Make covarianc... |
library(jpeg)
jpg<-readJPEG(source="getdata-jeff.jpg",native=TRUE)
quantile(jpg,probs = c(.3,.8)) | /02_Getting_and_Cleaning_Data/week3/q2.R | no_license | fhyme/Coursera_Data_Science | R | false | false | 97 | r | library(jpeg)
jpg<-readJPEG(source="getdata-jeff.jpg",native=TRUE)
quantile(jpg,probs = c(.3,.8)) |
# Useful Functions
source("functions_out.R")
source("functions_plot.R")
source("functions_power.R")
source("functions_string.R")
source("functions_tstats.R")
source("functions_wavelets.R")
source("functions_SPS.R")
quad.area <- function(x1, x2, y1, y2) {
t1 <- tri.area(x1, x2, y1)
t2 <- tri.area(x2, y1, y2)
... | /Power Simulations (ISERC Paper)/functions.R | no_license | morndorff/GoF-Test | R | false | false | 8,193 | r | # Useful Functions
source("functions_out.R")
source("functions_plot.R")
source("functions_power.R")
source("functions_string.R")
source("functions_tstats.R")
source("functions_wavelets.R")
source("functions_SPS.R")
quad.area <- function(x1, x2, y1, y2) {
t1 <- tri.area(x1, x2, y1)
t2 <- tri.area(x2, y1, y2)
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ancova.h.R
\name{ancova}
\alias{ancova}
\title{ANCOVA}
\usage{
ancova(data, dep, factors = NULL, covs = NULL, effectSize = NULL,
modelTest = FALSE, modelTerms = NULL, ss = "3", homo = FALSE,
norm = FALSE, qq = FALSE, contrasts = NULL, pos... | /man/ancova.Rd | no_license | cran/jmv | R | false | true | 5,477 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ancova.h.R
\name{ancova}
\alias{ancova}
\title{ANCOVA}
\usage{
ancova(data, dep, factors = NULL, covs = NULL, effectSize = NULL,
modelTest = FALSE, modelTerms = NULL, ss = "3", homo = FALSE,
norm = FALSE, qq = FALSE, contrasts = NULL, pos... |
context("Model Fitting")
source("generate_test_datasets.R")
# Generate data sets and compare results of fitDRModel to the result of nls and
# lm for AIC function (if these are consistent parameter estimates, residual
# sum of square and degrees of freedom are consistent) and the vcov function
# (if these are consiste... | /tests/testthat/test-fitMod.R | no_license | bbnkmp/DoseFinding | R | false | false | 13,655 | r | context("Model Fitting")
source("generate_test_datasets.R")
# Generate data sets and compare results of fitDRModel to the result of nls and
# lm for AIC function (if these are consistent parameter estimates, residual
# sum of square and degrees of freedom are consistent) and the vcov function
# (if these are consiste... |
## Copyright (c) 2016, James P. Howard, II <jh@jameshoward.us>
##
## Redistribution and use in source and binary forms, with or without
## modification, are permitted provided that the following conditions are
## met:
##
## Redistributions of source code must retain the above copyright
## notice, this list of c... | /R/cmna.R | no_license | helixcn/cmna | R | false | false | 2,085 | r | ## Copyright (c) 2016, James P. Howard, II <jh@jameshoward.us>
##
## Redistribution and use in source and binary forms, with or without
## modification, are permitted provided that the following conditions are
## met:
##
## Redistributions of source code must retain the above copyright
## notice, this list of c... |
summary(iris)
install.packages("sampling")
library(sampling)
#gerando estrato (conjunto de dados, vetor de colunas e vetor com tamanho dos estratos)
amostra_estrat = strata(iris, c("Species"), size=c(25,25,25), method="srswor")
summary(amostra_estrat)
summary(infert)
round(12 / 248 * 100)
round(120 / 248 * 100)
round... | /R/amostragem_estratificada.R | no_license | vinibfranc/CursoDataScience | R | false | false | 444 | r | summary(iris)
install.packages("sampling")
library(sampling)
#gerando estrato (conjunto de dados, vetor de colunas e vetor com tamanho dos estratos)
amostra_estrat = strata(iris, c("Species"), size=c(25,25,25), method="srswor")
summary(amostra_estrat)
summary(infert)
round(12 / 248 * 100)
round(120 / 248 * 100)
round... |
imputeCensored <-
function(data=NULL, estimator=makeLearner("regr.lm"), epsilon=0.1, maxit=1000) {
if(!testClass(estimator, "Learner")) {
stop("Need regressor to impute values!")
}
assertClass(data, "llama.data")
if(is.null(data$success)) {
stop("Need successes to impute censored values!... | /R/imputeCensored.R | no_license | cran/llama | R | false | false | 2,901 | r | imputeCensored <-
function(data=NULL, estimator=makeLearner("regr.lm"), epsilon=0.1, maxit=1000) {
if(!testClass(estimator, "Learner")) {
stop("Need regressor to impute values!")
}
assertClass(data, "llama.data")
if(is.null(data$success)) {
stop("Need successes to impute censored values!... |
# --- Effect of Italian govt spending shock on French exports
# Data period: 1980q1-2018q4
# 95% and 68% confidence intervals
# h = 4, 8 and 12
# OLS with left-hand side in growth rates and 4 lags of x(t-1)
source('~/Studie/MSc ECO/Period 5-6 MSc thesis/MSc thesis RStudio project/Scripts/Spillovers FR and IT... | /trade spillovers/Trade spillovers IT and FR v3 1.R | no_license | mdg9709/spilloversNL | R | false | false | 8,213 | r | # --- Effect of Italian govt spending shock on French exports
# Data period: 1980q1-2018q4
# 95% and 68% confidence intervals
# h = 4, 8 and 12
# OLS with left-hand side in growth rates and 4 lags of x(t-1)
source('~/Studie/MSc ECO/Period 5-6 MSc thesis/MSc thesis RStudio project/Scripts/Spillovers FR and IT... |
########################################################################
## Description: Loads functions used by mir_prep script
## Input(s)/Outputs(s): see individual functions
## How To Use: must be sourced by mir_prep script
########################################################################
library(here)
if (!... | /gbd_2019/cod_code/cancer/c_models/a_mi_ratio/mir_prep_functions.r | no_license | Nermin-Ghith/ihme-modeling | R | false | false | 27,161 | r | ########################################################################
## Description: Loads functions used by mir_prep script
## Input(s)/Outputs(s): see individual functions
## How To Use: must be sourced by mir_prep script
########################################################################
library(here)
if (!... |
library(phylosim)
### Name: getRateParamList.T92
### Title: Get the rate parameters
### Aliases: getRateParamList.T92 T92.getRateParamList
### getRateParamList,T92-method
### ** Examples
# create a T92 object
p<-T92()
# set/get rate parameters
setRateParamList(p,list(
"A... | /data/genthat_extracted_code/phylosim/examples/getRateParamList.T92.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 607 | r | library(phylosim)
### Name: getRateParamList.T92
### Title: Get the rate parameters
### Aliases: getRateParamList.T92 T92.getRateParamList
### getRateParamList,T92-method
### ** Examples
# create a T92 object
p<-T92()
# set/get rate parameters
setRateParamList(p,list(
"A... |
# TODO: Add comment
#
# Author: FWang9
###############################################################################
############Using ASCAT
############segmentation and estimate DNA copy number based on germline mutation
############the formate of inputdata were chr, position, refallele counts in tumor, a... | /DNAfunction.R | no_license | xtmgah/Texomer | R | false | false | 50,979 | r | # TODO: Add comment
#
# Author: FWang9
###############################################################################
############Using ASCAT
############segmentation and estimate DNA copy number based on germline mutation
############the formate of inputdata were chr, position, refallele counts in tumor, a... |
# tools for text analysis of pubmed data
# source: pubmed abstracts and metadata
# objective - create tools to information extraction, visualization and knowledge creation
### packages
library(tidyverse)
library(rentrez)
library(tidytext)
library(XML)
### querying pubmed
# example: septic shock
# date: the month of m... | /start.R | no_license | gusmmm/entrez_critical_care | R | false | false | 2,119 | r | # tools for text analysis of pubmed data
# source: pubmed abstracts and metadata
# objective - create tools to information extraction, visualization and knowledge creation
### packages
library(tidyverse)
library(rentrez)
library(tidytext)
library(XML)
### querying pubmed
# example: septic shock
# date: the month of m... |
## Below are two functions that are used to create a special
## object that stores a Matrix and cache's its inversion.
## This function creates a special "matrix" object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
i <- NULL
set <- function(y) {
x <<- y
i <<- NULL
}
get <-... | /cachematrix.R | no_license | sjtuyanyan/ProgrammingAssignment2 | R | false | false | 965 | r | ## Below are two functions that are used to create a special
## object that stores a Matrix and cache's its inversion.
## This function creates a special "matrix" object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
i <- NULL
set <- function(y) {
x <<- y
i <<- NULL
}
get <-... |
estimate.psf <-
function (outenv=parent.env(environment()),n.bins=1,bloom.bin=FALSE,n.sources=5e2,onlyContams=TRUE,bin.type='SNR.quan',
lo=20,hi=200,type='num',check.one.sky=length(point.sources)>5*n.sources,blend.tolerance=0.5,
mask.tolerance=0.0,radial.tolerance=25,all.limit=0.15,env=NULL,plot=FAL... | /R/estimate.psf.R | no_license | AngusWright/LAMBDAR | R | false | false | 20,979 | r | estimate.psf <-
function (outenv=parent.env(environment()),n.bins=1,bloom.bin=FALSE,n.sources=5e2,onlyContams=TRUE,bin.type='SNR.quan',
lo=20,hi=200,type='num',check.one.sky=length(point.sources)>5*n.sources,blend.tolerance=0.5,
mask.tolerance=0.0,radial.tolerance=25,all.limit=0.15,env=NULL,plot=FAL... |
unzip("rprog_data_ProgAssignment3-data.zip", exdir = "hospitals")
dir('hospitals')
setwd('hospitals')
data <- read.csv("outcome-of-care-measures.csv", colClasses = 'character')
head(data)
ncol(data)
nrow(data)
names(data)
# 30-day mortality is in col 11
data[, 11] <- as.numeric(data[, 11]) # change from ... | /assignment 3.R | no_license | PawFran/r-programming | R | false | false | 962 | r | unzip("rprog_data_ProgAssignment3-data.zip", exdir = "hospitals")
dir('hospitals')
setwd('hospitals')
data <- read.csv("outcome-of-care-measures.csv", colClasses = 'character')
head(data)
ncol(data)
nrow(data)
names(data)
# 30-day mortality is in col 11
data[, 11] <- as.numeric(data[, 11]) # change from ... |
library(survcomp)
library(genefu)
# censor time in years#
censorTime <- 10
args <- (commandArgs(TRUE))
if(length(args)==0){
dataSets <- c('tothill2008')
}else{
dataSets <- NULL
for(i in 1:length(args)){
if(i == 1){
saveres <- args[[i]]
} else {
dataSets <- c( dataSets,... | /r_code/stem_like/GENIUS_gene_sig_extract.R | no_license | xulijunji/GENIUS_ovarian | R | false | false | 3,720 | r | library(survcomp)
library(genefu)
# censor time in years#
censorTime <- 10
args <- (commandArgs(TRUE))
if(length(args)==0){
dataSets <- c('tothill2008')
}else{
dataSets <- NULL
for(i in 1:length(args)){
if(i == 1){
saveres <- args[[i]]
} else {
dataSets <- c( dataSets,... |
# Similar to single picto but has more flexibility with text labels.
# Arguments are designed to match with PrettyNumber
#' @importFrom verbs Sum
iconsWithText <- function (x,
total.icons = NA,
image = "star",
base.image = "",
... | /R/iconswithtext.R | no_license | Displayr/flipPictographs | R | false | false | 12,690 | r | # Similar to single picto but has more flexibility with text labels.
# Arguments are designed to match with PrettyNumber
#' @importFrom verbs Sum
iconsWithText <- function (x,
total.icons = NA,
image = "star",
base.image = "",
... |
library(tidyverse)
murders <- read_csv("data/murders.csv")
murders <- murders %>% mutate(region = factor(region), rate=total/population*10^5)
save(murders,file = "rda/murders.rda") | /wrangle-data.R | no_license | dlwlals0101/murders | R | false | false | 180 | r | library(tidyverse)
murders <- read_csv("data/murders.csv")
murders <- murders %>% mutate(region = factor(region), rate=total/population*10^5)
save(murders,file = "rda/murders.rda") |
Relocation section '\.rela\.plt' at offset .* contains 2 entries:
Offset Info Type Sym\.Value Sym\. Name \+ Addend
0008140c .*a4 R_SH_JMP_SLOT 00080c4c _sglobal \+ 0
00081410 .*a4 R_SH_JMP_SLOT 00000000 _sexternal \+ 0
Relocation section '\.rela\.dyn' at offset .* contains 4 entries:... | /external/binutils-2.38/ld/testsuite/ld-sh/vxworks1-lib.rd | permissive | zhmu/ananas | R | false | false | 610 | rd |
Relocation section '\.rela\.plt' at offset .* contains 2 entries:
Offset Info Type Sym\.Value Sym\. Name \+ Addend
0008140c .*a4 R_SH_JMP_SLOT 00080c4c _sglobal \+ 0
00081410 .*a4 R_SH_JMP_SLOT 00000000 _sexternal \+ 0
Relocation section '\.rela\.dyn' at offset .* contains 4 entries:... |
context("canvasXpress LegendPosition")
default_legend_position <- "right"
all_legend_positions <- c("topRight", "right", "bottomRight", "bottom", "bottomLeft", "left", "topLeft", "top")
inside_legend_only_positions <- c("topRight", "bottomRight", "bottomLeft", "topLeft")
segregated_legend_positions <- c(... | /tests/testthat/test-other-legend-position.R | no_license | kar-agg-gen/canvasXpress | R | false | false | 8,930 | r | context("canvasXpress LegendPosition")
default_legend_position <- "right"
all_legend_positions <- c("topRight", "right", "bottomRight", "bottom", "bottomLeft", "left", "topLeft", "top")
inside_legend_only_positions <- c("topRight", "bottomRight", "bottomLeft", "topLeft")
segregated_legend_positions <- c(... |
#' query UI Function
#'
#' @description A shiny Module.
#'
#' @param id,input,output,session Internal parameters for {shiny}.
#'
#' @noRd
#'
#' @import RSQLite
#' @importFrom shiny NS
#' @importFrom shinyjqui jqui_resizable
#' @importFrom shinyAce aceEditor
#' @importFrom DT DTOutput
#' @importFrom DT rend... | /R/mod_query.R | no_license | cran/rsqliteadmin | R | false | false | 12,822 | r | #' query UI Function
#'
#' @description A shiny Module.
#'
#' @param id,input,output,session Internal parameters for {shiny}.
#'
#' @noRd
#'
#' @import RSQLite
#' @importFrom shiny NS
#' @importFrom shinyjqui jqui_resizable
#' @importFrom shinyAce aceEditor
#' @importFrom DT DTOutput
#' @importFrom DT rend... |
# Data visualiations for Alpha, Beta, and Gamma diversity in Sphagnum peat bogs
# Population & Community Ecology - Year 3
# Emma Gemal, s1758915@sms.ed.ac.uk
# 19/11/2019
# Library ----
library(tidyverse)
# Creating the diversity data frame ----
mesocosm <- c(rep("one", 3), rep("two", 3), rep("pooled", 3)) %>%
... | /Script/sphagnum_plots.R | permissive | emmagemal/PCE | R | false | false | 2,491 | r | # Data visualiations for Alpha, Beta, and Gamma diversity in Sphagnum peat bogs
# Population & Community Ecology - Year 3
# Emma Gemal, s1758915@sms.ed.ac.uk
# 19/11/2019
# Library ----
library(tidyverse)
# Creating the diversity data frame ----
mesocosm <- c(rep("one", 3), rep("two", 3), rep("pooled", 3)) %>%
... |
# TODO: Add comment
#
# Author: ajinkya
###############################################################################
getPeriodReturnSignals <- function(ticker,timeFrequency,percent)
{
#percent.absolute <- (percent/100)
percent.absolute <- percent
print(percent.absolute)
print(" calculating daily return sig... | /srs-cran/src/technicalindicators/TickerDailyReturns.R | no_license | ajinkya-github/stocksimulation | R | false | false | 1,655 | r | # TODO: Add comment
#
# Author: ajinkya
###############################################################################
getPeriodReturnSignals <- function(ticker,timeFrequency,percent)
{
#percent.absolute <- (percent/100)
percent.absolute <- percent
print(percent.absolute)
print(" calculating daily return sig... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/biglm_mapper.R
\name{cluster_se}
\alias{cluster_se}
\title{Map-reduce clustered standard errors with \code{biglm}}
\usage{
cluster_se(file_list, fitted_model, ...)
}
\arguments{
\item{file_list}{Character vector of data file names. Must be in... | /man/cluster_se.Rd | no_license | gregobad/biglm-mapper | R | false | true | 1,248 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/biglm_mapper.R
\name{cluster_se}
\alias{cluster_se}
\title{Map-reduce clustered standard errors with \code{biglm}}
\usage{
cluster_se(file_list, fitted_model, ...)
}
\arguments{
\item{file_list}{Character vector of data file names. Must be in... |
library(tm)
library(wordcloud)
library(memoise)
# We load serveral books.
books <<- list("A Mid Summer Night's Dream" = "summer",
"The Merchant of Venice" = "merchant",
"Romeo and Juliet" = "romeo")
# Using memoise function to automatically cache the results
getTermMatrix <- me... | /Developing_data_products/Project_course/global.R | no_license | pvmontes/datasciencecoursera | R | false | false | 955 | r | library(tm)
library(wordcloud)
library(memoise)
# We load serveral books.
books <<- list("A Mid Summer Night's Dream" = "summer",
"The Merchant of Venice" = "merchant",
"Romeo and Juliet" = "romeo")
# Using memoise function to automatically cache the results
getTermMatrix <- me... |
getwd()
setwd("C:\\Users\\minahm\\Documents\\School\\Fall 2014\\CMDA 3654")
load('phsample.RData')
#The data is an anonymized dataset of a person/household containing the information
#Age, Employment class, Education Level, Sex of Worker
#Selects a subset that is self-described fulltime
#working 40 hours a week atle... | /minahm92_hw2.r | no_license | kim-minahm/CMDA-3654 | R | false | false | 1,921 | r |
getwd()
setwd("C:\\Users\\minahm\\Documents\\School\\Fall 2014\\CMDA 3654")
load('phsample.RData')
#The data is an anonymized dataset of a person/household containing the information
#Age, Employment class, Education Level, Sex of Worker
#Selects a subset that is self-described fulltime
#working 40 hours a week atle... |
#' Preprocessing of TNS class objects.
#'
#' Creates TNS class onbjects for regulons an survival data.
#'
#' @param tni A \linkS4class{TNI} class, already processed with the same samples
#' listed in the survival data.frame.
#' @param survivalData A named data.frame with samples in rows and survival data
#' in the co... | /R/AllMethods.R | no_license | xtsvm/RTNsurvival | R | false | false | 21,136 | r |
#' Preprocessing of TNS class objects.
#'
#' Creates TNS class onbjects for regulons an survival data.
#'
#' @param tni A \linkS4class{TNI} class, already processed with the same samples
#' listed in the survival data.frame.
#' @param survivalData A named data.frame with samples in rows and survival data
#' in the co... |
# clumsy plot code to be revised
## plots: PlotFaces (Chernoff-Faces) ====
# aus TeachingDemos, Author: H. P. Wolf
# updated with newer version, edited and simplified by 0.99.24
# Source aplpack, Author: H. P. Wolf
#' Chernoff Faces
#'
#' Plot Chernoff faces. The rows of a data matrix represent ca... | /R/SpecialPlots.r | no_license | forked-packages/DescTools--2 | R | false | false | 88,287 | r | # clumsy plot code to be revised
## plots: PlotFaces (Chernoff-Faces) ====
# aus TeachingDemos, Author: H. P. Wolf
# updated with newer version, edited and simplified by 0.99.24
# Source aplpack, Author: H. P. Wolf
#' Chernoff Faces
#'
#' Plot Chernoff faces. The rows of a data matrix represent ca... |
#' Log-Likelihood Function for Parametric Lifetime Distributions
#'
#' @description
#' This function computes the log-likelihood value with respect to a given set
#' of parameters. In terms of *Maximum Likelihood Estimation* this function can
#' be optimized ([optim][stats::optim]) to estimate the parameters and
#' var... | /R/likelihood_functions.R | no_license | Tim-TU/weibulltools | R | false | false | 11,059 | r | #' Log-Likelihood Function for Parametric Lifetime Distributions
#'
#' @description
#' This function computes the log-likelihood value with respect to a given set
#' of parameters. In terms of *Maximum Likelihood Estimation* this function can
#' be optimized ([optim][stats::optim]) to estimate the parameters and
#' var... |
#Stat R 502 Final Project
# Data manipulation and cleaning
Projectraw <- read.csv("train.csv")
Titanic.data <- read.csv("train.csv")
View(Projectraw)
dim(Projectraw)
Titanic.data %<>% na.omit
str(Titanic.data)
##making the response variable a categorical response.
Titanic.data$Survived %<>% as.factor
##making clas... | /Logisitic_Regression/502_Project_Files/Final_Code/data_manipulation.R | no_license | SherberttheScientist/R-Statistics | R | false | false | 3,708 | r | #Stat R 502 Final Project
# Data manipulation and cleaning
Projectraw <- read.csv("train.csv")
Titanic.data <- read.csv("train.csv")
View(Projectraw)
dim(Projectraw)
Titanic.data %<>% na.omit
str(Titanic.data)
##making the response variable a categorical response.
Titanic.data$Survived %<>% as.factor
##making clas... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/databases.R
\name{load_db_deprecated}
\alias{load_db_deprecated}
\title{Load Database connections into Global Environment}
\usage{
load_db_deprecated(name = NULL)
}
\arguments{
\item{name}{(OPTIONAL) name of ODBC database source}
}
\value{
Co... | /man/load_db_deprecated.Rd | permissive | dshurick/shurtools | R | false | true | 410 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/databases.R
\name{load_db_deprecated}
\alias{load_db_deprecated}
\title{Load Database connections into Global Environment}
\usage{
load_db_deprecated(name = NULL)
}
\arguments{
\item{name}{(OPTIONAL) name of ODBC database source}
}
\value{
Co... |
library(ape)
testtree <- read.tree("2021_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="2021_0_unrooted.txt") | /codeml_files/newick_trees_processed/2021_0/rinput.R | no_license | DaniBoo/cyanobacteria_project | R | false | false | 135 | r | library(ape)
testtree <- read.tree("2021_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="2021_0_unrooted.txt") |
rm(list=ls())
require(readxl)
require(reshape2)
require(ggplot2)
require(GGally)
require(factoextra)
ADD_PLOT_CONSTRAINTS=T
INCLUDE_LOG_SCALE_TRACE=F
DATE = "2021-05-04"
# Read in Gelman-Rubin RHat results
if(file.exists(paste(DATE, '_MCMCSTATmprsf_Diagnostics.xlsx', sep='', collapse=''))){
df.prsf = data.frame(rea... | /MCMC_CODE/Matlab/MCMC_Visualize_traces.R | no_license | lopmanlab/Serological_Shielding | R | false | false | 6,574 | r | rm(list=ls())
require(readxl)
require(reshape2)
require(ggplot2)
require(GGally)
require(factoextra)
ADD_PLOT_CONSTRAINTS=T
INCLUDE_LOG_SCALE_TRACE=F
DATE = "2021-05-04"
# Read in Gelman-Rubin RHat results
if(file.exists(paste(DATE, '_MCMCSTATmprsf_Diagnostics.xlsx', sep='', collapse=''))){
df.prsf = data.frame(rea... |
#' Johnson-Lewin model
#'
#'
#' @param temp temperature in degrees centigrade
#' @param e activation energy (eV)
#' @param eh high temperature de-activation energy (eV)
#' @param topt optimum temperature (K)
#' @param r0 scaling parameter
#' @author Daniel Padfield
#' @references Johnson, Frank H., and Isaac Lewin. "Th... | /R/johnsonlewin_1946.R | no_license | juadiegaitan/rTPC | R | false | false | 793 | r | #' Johnson-Lewin model
#'
#'
#' @param temp temperature in degrees centigrade
#' @param e activation energy (eV)
#' @param eh high temperature de-activation energy (eV)
#' @param topt optimum temperature (K)
#' @param r0 scaling parameter
#' @author Daniel Padfield
#' @references Johnson, Frank H., and Isaac Lewin. "Th... |
library(readr)
library(data.table)
library(proxy)
library(qlcMatrix)
library(cccd)
library(igraph)
setwd("/home/branden/Documents/kaggle/walmart")
# Load data
ts1Trans <- data.table(read_csv("./data_trans/ts1Trans3_netScans_abs.csv"))
# Department distance/similarity
ts1_dept <- as.matrix(ts1Trans[, 47:115, with=FALSE... | /walmart/data_trans/dist_sim_abs.R | no_license | brandenkmurray/kaggle | R | false | false | 2,049 | r | library(readr)
library(data.table)
library(proxy)
library(qlcMatrix)
library(cccd)
library(igraph)
setwd("/home/branden/Documents/kaggle/walmart")
# Load data
ts1Trans <- data.table(read_csv("./data_trans/ts1Trans3_netScans_abs.csv"))
# Department distance/similarity
ts1_dept <- as.matrix(ts1Trans[, 47:115, with=FALSE... |
library(h2o)
iris.hex <- as.h2o(iris)
iris.gbm <- h2o.gbm(y="Species", training_frame=iris.hex, model_id="irisgbm")
h2o.download_mojo(model=iris.gbm, path="/Users/nkkarpov/ws", get_genmodel_jar=TRUE) | /tutorials/mojo-resource/train_and_export_model.R | no_license | h2oai/h2o-tutorials | R | false | false | 199 | r | library(h2o)
iris.hex <- as.h2o(iris)
iris.gbm <- h2o.gbm(y="Species", training_frame=iris.hex, model_id="irisgbm")
h2o.download_mojo(model=iris.gbm, path="/Users/nkkarpov/ws", get_genmodel_jar=TRUE) |
#' Elo rating function.
#'
#' @param games Dataframe containing games (1 row each) with
#' columns for players i and j and a column for the results
#' @param PROB Function to compute the probabilities. Should
#' take in two skills and optionally other parameters and return
#' a pairwise win/loss probability.
#'... | /Rating Functions/Rate_Elo_01.R | no_license | alexm496/ranking | R | false | false | 1,139 | r | #' Elo rating function.
#'
#' @param games Dataframe containing games (1 row each) with
#' columns for players i and j and a column for the results
#' @param PROB Function to compute the probabilities. Should
#' take in two skills and optionally other parameters and return
#' a pairwise win/loss probability.
#'... |
# Shiny Price_production
library(data.table)
library(shiny)
library(ggplot2)
library(dplyr)
library(shiny)
library(tidyr)
library(stringr)
#### The UI ####
ui <- fluidPage(
titlePanel(title = "Worldside Crop Price vs. Production Trends",
windowTitle = "Price X Production"),
sidebarLayout(
sideb... | /Shiny_price_prod.R | no_license | TakaakiKihara/Group_Project_Agriculture | R | false | false | 3,177 | r | # Shiny Price_production
library(data.table)
library(shiny)
library(ggplot2)
library(dplyr)
library(shiny)
library(tidyr)
library(stringr)
#### The UI ####
ui <- fluidPage(
titlePanel(title = "Worldside Crop Price vs. Production Trends",
windowTitle = "Price X Production"),
sidebarLayout(
sideb... |
#' Resample Di-ZTD to phase cell resolution and match raster extents.
#' @author Subhadip Datta
#' @param unw_pha Un-wrapped InSAR tile/raster.
#' @param dztd Di-ZTD.
#' @param method Raster resampleing method "ngb" for nearest neighbor or "bilinear" for bilinear interpolation
#' @import raster
#' @examples
#' ... | /R/downsample_dztd.R | no_license | cran/GInSARCorW | R | false | false | 1,016 | r | #' Resample Di-ZTD to phase cell resolution and match raster extents.
#' @author Subhadip Datta
#' @param unw_pha Un-wrapped InSAR tile/raster.
#' @param dztd Di-ZTD.
#' @param method Raster resampleing method "ngb" for nearest neighbor or "bilinear" for bilinear interpolation
#' @import raster
#' @examples
#' ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/create_lags.R
\name{create_lags}
\alias{create_lags}
\title{Create Lag Variables}
\usage{
create_lags(data, lags, vars)
}
\arguments{
\item{data}{A data frame.}
\item{lags}{A numeric vector of lags.}
\item{vars}{A character vector of column... | /man/create_lags.Rd | no_license | ebrist/mlts | R | false | true | 666 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/create_lags.R
\name{create_lags}
\alias{create_lags}
\title{Create Lag Variables}
\usage{
create_lags(data, lags, vars)
}
\arguments{
\item{data}{A data frame.}
\item{lags}{A numeric vector of lags.}
\item{vars}{A character vector of column... |
prescribe<-function(m,m3){ifelse((m$"Harvesting.System")=="Cable Manual WT", yarderEst(m,m3),
ifelse((m$"Harvesting.System")=="Ground-Based Man WT", sawSkidEst(m,m3),
ifelse((m$"Harvesting.System")=="Ground-Based Mech WT", fbSkidEst(m,m3),
... | /fvsopcostshiny.r | no_license | timgholland/ltw | R | false | false | 30,714 | r |
prescribe<-function(m,m3){ifelse((m$"Harvesting.System")=="Cable Manual WT", yarderEst(m,m3),
ifelse((m$"Harvesting.System")=="Ground-Based Man WT", sawSkidEst(m,m3),
ifelse((m$"Harvesting.System")=="Ground-Based Mech WT", fbSkidEst(m,m3),
... |
## Put comments here that give an overall description of what your
## functions do
## This function creates a special "matrix" object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
set <- function(y) {
x <<- y
m <<- NULL
}
... | /cachematrix.R | no_license | zysuper/ProgrammingAssignment2 | R | false | false | 1,092 | r | ## Put comments here that give an overall description of what your
## functions do
## This function creates a special "matrix" object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
set <- function(y) {
x <<- y
m <<- NULL
}
... |
library(dplyr)
library(DataExplorer)
library(ggplot2)
library(plotly)
library(data.table)
library(zipcode)
library(tidyverse)
library(stringr)
library(maps)
library(kableExtra)
library(RcppRoll)
library(plotly)
library(GGally)
### Parsing only numbers from drug definition ###
parse_num <- function(df){
df1 <- df %... | /week5/health-functions.R | no_license | yerin-flora/AnomalyDetection | R | false | false | 1,793 | r | library(dplyr)
library(DataExplorer)
library(ggplot2)
library(plotly)
library(data.table)
library(zipcode)
library(tidyverse)
library(stringr)
library(maps)
library(kableExtra)
library(RcppRoll)
library(plotly)
library(GGally)
### Parsing only numbers from drug definition ###
parse_num <- function(df){
df1 <- df %... |
############### sysVarInPlots
#' Produces plots for interpreting the results from sysVarIn.
#'
#' @param fullData A dataframe created by the "makeFullData" function.
#' @param sysVar_name The name of the variable in the dataframe that contains the system variable.
#' @param sysVarType Whether the system variable is "... | /R/sysVarPlots.R | no_license | ebmtnprof/rties | R | false | false | 18,480 | r |
############### sysVarInPlots
#' Produces plots for interpreting the results from sysVarIn.
#'
#' @param fullData A dataframe created by the "makeFullData" function.
#' @param sysVar_name The name of the variable in the dataframe that contains the system variable.
#' @param sysVarType Whether the system variable is "... |
getMovingAverageResult <- function(x){
recorded_close_test <- final_return[[6]]
predicted_close_test <- final_return[[8]]
ma_close <- SMA(append(final_return[[4]], final_return[[8]]), n=7)[test_split_index:n_instances]
budget <- init_budget
stocks_held <- 0
for(i in 1:length(predicted_close_test)){... | /ma.R | no_license | liamdx/GA-NN-AlgorithmicTrading | R | false | false | 922 | r | getMovingAverageResult <- function(x){
recorded_close_test <- final_return[[6]]
predicted_close_test <- final_return[[8]]
ma_close <- SMA(append(final_return[[4]], final_return[[8]]), n=7)[test_split_index:n_instances]
budget <- init_budget
stocks_held <- 0
for(i in 1:length(predicted_close_test)){... |
# Load and do basic data munging on fraternity surveys.
library(tidyverse)
library(here)
# Clean user table -----
user <- read_csv(here("data/PRIVATEDATA/user.csv")) %>%
select(
id, fbid = fb_id, zip, from = location_from, at = lives_in, age, gender, race,
collected = collected_friends_size, fraternity_id
... | /rscripts/datacleaner.R | no_license | gregmacfarlane/facebookfraternities | R | false | false | 2,193 | r | # Load and do basic data munging on fraternity surveys.
library(tidyverse)
library(here)
# Clean user table -----
user <- read_csv(here("data/PRIVATEDATA/user.csv")) %>%
select(
id, fbid = fb_id, zip, from = location_from, at = lives_in, age, gender, race,
collected = collected_friends_size, fraternity_id
... |
context("Polling progress")
with_mock_HTTP({
test_that("If progress polling gives up, it tells you what to do", {
with(temp.option(crunch.timeout=0.5), {
expect_error(pollProgress("/api/progress/1.json", wait=0.25),
paste('Your process is still running on the server. It is',
... | /crunch/tests/testthat/test-progress.R | no_license | ingted/R-Examples | R | false | false | 1,430 | r | context("Polling progress")
with_mock_HTTP({
test_that("If progress polling gives up, it tells you what to do", {
with(temp.option(crunch.timeout=0.5), {
expect_error(pollProgress("/api/progress/1.json", wait=0.25),
paste('Your process is still running on the server. It is',
... |
require(matlab)
require(PEIP)
require(Matrix)
require(pracma)
fast_BSF_G_sampler = function(burn, sp, thin, b0, b1, h2_divisions, epsilon, priors, draw_iter, Y, Z_1, Z_2, X){
#% -- Daniel Runcie -- %
#% Gibbs sampler for genetic covariance estimation based on mixed effects
#% model, with missing data
#% Ba... | /BSF-G_R/fast_BSF_G_sampler.R | no_license | lrshum17/MukherjeeRuncieRCode | R | false | false | 18,346 | r | require(matlab)
require(PEIP)
require(Matrix)
require(pracma)
fast_BSF_G_sampler = function(burn, sp, thin, b0, b1, h2_divisions, epsilon, priors, draw_iter, Y, Z_1, Z_2, X){
#% -- Daniel Runcie -- %
#% Gibbs sampler for genetic covariance estimation based on mixed effects
#% model, with missing data
#% Ba... |
#' This R script will process all R mardown files (those with in_ext file extention,
#' .Rmd by default) in the current working directory. Files with a status of
#' 'processed' will be converted to markdown (with out_ext file extention, '.md'
#' by default). It will change the published parameter to 'true' and change t... | /rmarkdown.r | no_license | jarad/jarad.github.com | R | false | false | 2,551 | r | #' This R script will process all R mardown files (those with in_ext file extention,
#' .Rmd by default) in the current working directory. Files with a status of
#' 'processed' will be converted to markdown (with out_ext file extention, '.md'
#' by default). It will change the published parameter to 'true' and change t... |
#' Simulated group markers
#'
#' This function gives you the ranked list of group markers at the specified
#' proportion of top markers (specificity)
#'
#' @param rank_df The data frame with the ranked group genes as returned by the
#' [rank_sim()] function.
#' @param spec The proportion of top ranked genes. It has to ... | /R/markers_by_specificity.R | permissive | crsky1023/matchSCore2 | R | false | false | 1,273 | r | #' Simulated group markers
#'
#' This function gives you the ranked list of group markers at the specified
#' proportion of top markers (specificity)
#'
#' @param rank_df The data frame with the ranked group genes as returned by the
#' [rank_sim()] function.
#' @param spec The proportion of top ranked genes. It has to ... |
## Preliminaries
rm(list=ls())
# Change working directory to where you've stored ZTRAX
path<- "P:/Peter/Hedonics/Groundwater/"
#install.packages("dplyr", repos = "http://mran.revolutionanalytics.com")
## This function will check if a package is installed, and if not, install it
pkgTest <- function(x) {
... | /AnalyzeNYall.R | no_license | astevens186/hedonics | R | false | false | 98,734 | r |
## Preliminaries
rm(list=ls())
# Change working directory to where you've stored ZTRAX
path<- "P:/Peter/Hedonics/Groundwater/"
#install.packages("dplyr", repos = "http://mran.revolutionanalytics.com")
## This function will check if a package is installed, and if not, install it
pkgTest <- function(x) {
... |
x=c(0,1,2,3,4,5)
y=x*2
plot(x,y)
| /Lesson 1 code.R | no_license | jboyd8/r_footbalanalytics_course | R | false | false | 35 | r | x=c(0,1,2,3,4,5)
y=x*2
plot(x,y)
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MethComp-package.R
\docType{data}
\name{sbp.MC}
\alias{sbp.MC}
\title{A MCmcmc object from the sbp data}
\format{
The format is a \code{\link{MCmcmc}} object.
}
\description{
This object is included for illustrative purposes. It is a result o... | /man/sbp.MC.Rd | no_license | ekstroem/MethComp | R | false | true | 1,511 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MethComp-package.R
\docType{data}
\name{sbp.MC}
\alias{sbp.MC}
\title{A MCmcmc object from the sbp data}
\format{
The format is a \code{\link{MCmcmc}} object.
}
\description{
This object is included for illustrative purposes. It is a result o... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/asciiart.R
\name{asciiart}
\alias{asciiart}
\title{Create asciiart image}
\usage{
asciiart(
file,
width = 80,
text_scaling = 1,
out_width = 8,
out_name = NULL,
text_col = "black",
chars = c("@", "\%", "#", "*", "+", "=", "-", ":... | /man/asciiart.Rd | no_license | cj-holmes/asciiart | R | false | true | 1,656 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/asciiart.R
\name{asciiart}
\alias{asciiart}
\title{Create asciiart image}
\usage{
asciiart(
file,
width = 80,
text_scaling = 1,
out_width = 8,
out_name = NULL,
text_col = "black",
chars = c("@", "\%", "#", "*", "+", "=", "-", ":... |
#-------------------------------------------------------------------------------
# Copyright (c) 2012 University of Illinois, NCSA.
# All rights reserved. This program and the accompanying materials
# are made available under the terms of the
# University of Illinois/NCSA Open Source License
# which accompanies this d... | /utils/R/ensemble.R | permissive | jingxia/pecan | R | false | false | 10,648 | r | #-------------------------------------------------------------------------------
# Copyright (c) 2012 University of Illinois, NCSA.
# All rights reserved. This program and the accompanying materials
# are made available under the terms of the
# University of Illinois/NCSA Open Source License
# which accompanies this d... |
BFS <- function (A, r=nrow(A)) {
if (!is.matrix(A) || nrow(A) != ncol(A)) stop("A must be a square matrix")
if (nrow(A) <= 1) return(matrix(0,nrow(A),ncol(A)))
if (nrow(A) < r) stop("r must be a natural number <= number of rows of A")
out <- 0*A
disc <- rep(FALSE, nrow(A))
disc[r] <- TRUE
queue <- r
... | /R/utility.R | no_license | rje42/dependence | R | false | false | 1,512 | r | BFS <- function (A, r=nrow(A)) {
if (!is.matrix(A) || nrow(A) != ncol(A)) stop("A must be a square matrix")
if (nrow(A) <= 1) return(matrix(0,nrow(A),ncol(A)))
if (nrow(A) < r) stop("r must be a natural number <= number of rows of A")
out <- 0*A
disc <- rep(FALSE, nrow(A))
disc[r] <- TRUE
queue <- r
... |
options(stringsAsFactors=F)
library(GenomicRanges)
base = "70PRS/03PRSinput/GWAS/iPSYCHPGC_HG38_update_model1QC_EUR_only_noMHC_MAF005"
prs_base = read.table(base,header=T,sep="\t")
prs_base_GR = GRanges(prs_base$CHR,IRanges(prs_base$BP,prs_base$BP))
mcols(prs_base_GR) = prs_base[,c(3,4,6:9)]
prs_snp = read.table("70P... | /PRS/7B_4.extractPRSSNP_fromBase.R | no_license | thewonlab/GWAS_ASD_SPARK | R | false | false | 674 | r | options(stringsAsFactors=F)
library(GenomicRanges)
base = "70PRS/03PRSinput/GWAS/iPSYCHPGC_HG38_update_model1QC_EUR_only_noMHC_MAF005"
prs_base = read.table(base,header=T,sep="\t")
prs_base_GR = GRanges(prs_base$CHR,IRanges(prs_base$BP,prs_base$BP))
mcols(prs_base_GR) = prs_base[,c(3,4,6:9)]
prs_snp = read.table("70P... |
# Autor: Ing. Adrian Huerta
rm(list = ls())
`%>%` = magrittr::`%>%`
path = "C:/Fernando Pastor/Adrian_scripts/02_entregable/02_gridded/scripts/"
setwd(path)
## Funciones
source('functions.R')
path2 = "C:/Fernando Pastor/Adrian_scripts/02_entregable/02_gridded/dataset/OBS/TO_send/"
setwd(path2)
## Datos observados de ... | /example.R | no_license | jonathan123pastor/Temperatures_by_Adrian_Huerta | R | false | false | 2,526 | r | # Autor: Ing. Adrian Huerta
rm(list = ls())
`%>%` = magrittr::`%>%`
path = "C:/Fernando Pastor/Adrian_scripts/02_entregable/02_gridded/scripts/"
setwd(path)
## Funciones
source('functions.R')
path2 = "C:/Fernando Pastor/Adrian_scripts/02_entregable/02_gridded/dataset/OBS/TO_send/"
setwd(path2)
## Datos observados de ... |
x <- read.csv("household_power_consumption.txt", sep = ";")
simple <-
subset(x,
Date == "1/2/2007" |
Date == "2/2/2007",
select = c(Global_active_power))
n <- simple$Global_active_power
png("plot1.png", width = 480, height = 480)
hist(
x = as.numeric(levels(n))[n],
col = "Red",
... | /plot_1.R | no_license | kvnch/ExData_Plotting1 | R | false | false | 405 | r | x <- read.csv("household_power_consumption.txt", sep = ";")
simple <-
subset(x,
Date == "1/2/2007" |
Date == "2/2/2007",
select = c(Global_active_power))
n <- simple$Global_active_power
png("plot1.png", width = 480, height = 480)
hist(
x = as.numeric(levels(n))[n],
col = "Red",
... |
#' Identify phosphorylation regulation influence downstream
#'
#' This function identifies the downstream regulation influence
#' of phosphoprotein regulation for further downstream analysis steps.
#'
#' @param data_omics_plus output list of readPWdata function; first element
#' contains an OmicsData object, secons e... | /R/pwOmics_downstream_analysis.R | no_license | MarenS2/pwOmics | R | false | false | 10,359 | r | #' Identify phosphorylation regulation influence downstream
#'
#' This function identifies the downstream regulation influence
#' of phosphoprotein regulation for further downstream analysis steps.
#'
#' @param data_omics_plus output list of readPWdata function; first element
#' contains an OmicsData object, secons e... |
##
### ---------------
###
### Create: Jianming Zeng
### Date: 2019-07-24 15:03:19
### Email: jmzeng1314@163.com
### Blog: http://www.bio-info-trainee.com/
### Forum: http://www.biotrainee.com/thread-1376-1-1.html
### CAFS/SUSTC/Eli Lilly/University of Macau
### Update Log: 2019-07-24 First version
###
### ---------... | /step3-HLA-in-tumor-of-patient1.R | no_license | zhaohongqiangsoliva/scRNA_10X | R | false | false | 1,462 | r | ##
### ---------------
###
### Create: Jianming Zeng
### Date: 2019-07-24 15:03:19
### Email: jmzeng1314@163.com
### Blog: http://www.bio-info-trainee.com/
### Forum: http://www.biotrainee.com/thread-1376-1-1.html
### CAFS/SUSTC/Eli Lilly/University of Macau
### Update Log: 2019-07-24 First version
###
### ---------... |
library(SenSrivastava)
### Name: E9.11
### Title: Data on Transit Privatization
### Aliases: E9.11
### Keywords: datasets
### ** Examples
data(E9.11)
summary(E9.11)
plot(E9.11)
| /data/genthat_extracted_code/SenSrivastava/examples/E9.11.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 184 | r | library(SenSrivastava)
### Name: E9.11
### Title: Data on Transit Privatization
### Aliases: E9.11
### Keywords: datasets
### ** Examples
data(E9.11)
summary(E9.11)
plot(E9.11)
|
#' Check Levels
#'
#' Checks the levels in a factor including the order and
#' whether other levels are permitted.
#'
#' @param x The object to check.
#' @param levels A character vector of the levels.
#' @param exclusive A flag indicating whether other levels are not permitted.
#' @param order A flag indicating whet... | /R/levels.R | permissive | cran/checkr | R | false | false | 2,137 | r | #' Check Levels
#'
#' Checks the levels in a factor including the order and
#' whether other levels are permitted.
#'
#' @param x The object to check.
#' @param levels A character vector of the levels.
#' @param exclusive A flag indicating whether other levels are not permitted.
#' @param order A flag indicating whet... |
#' Returns the relevant featureIds for a given geneset.
#'
#' @description
#' Gene sets are defined by the unique compound key consisting of their
#' `collection` and `name`. To fetch the featureIds associated with
#' a specific geneset, you must provide values for `i` and `j`. If
#' these are missing, then a character... | /R/AllGenerics.R | permissive | gladkia/sparrow | R | false | false | 12,849 | r | #' Returns the relevant featureIds for a given geneset.
#'
#' @description
#' Gene sets are defined by the unique compound key consisting of their
#' `collection` and `name`. To fetch the featureIds associated with
#' a specific geneset, you must provide values for `i` and `j`. If
#' these are missing, then a character... |
#' Calculate Weighted Standard Deviation
#'
#' Function to calculate weighted standard deviation.
#' @param x The observations to calculate the standard deviations from
#' @param w The weights associated with each observation.
#' @param na.rm If \code{TRUE}, then NA values will be removed.
weighted.sd <- function(x, w,... | /R/calc_projections.R | no_license | SirChancelot222/ffanalytics | R | false | false | 22,747 | r | #' Calculate Weighted Standard Deviation
#'
#' Function to calculate weighted standard deviation.
#' @param x The observations to calculate the standard deviations from
#' @param w The weights associated with each observation.
#' @param na.rm If \code{TRUE}, then NA values will be removed.
weighted.sd <- function(x, w,... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/paws.R
\name{detective}
\alias{detective}
\title{Amazon Detective}
\usage{
detective(config = list())
}
\arguments{
\item{config}{Optional configuration of credentials, endpoint, and/or region.
\itemize{
\item{\strong{access_key_id}:} {AWS ac... | /man/detective.Rd | no_license | cran/paws | R | false | true | 9,236 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/paws.R
\name{detective}
\alias{detective}
\title{Amazon Detective}
\usage{
detective(config = list())
}
\arguments{
\item{config}{Optional configuration of credentials, endpoint, and/or region.
\itemize{
\item{\strong{access_key_id}:} {AWS ac... |
\name{TES}
\alias{TES}
\title{
Calculate the total environ storage.
}
\description{
Calculates the total storage in each n input and output environs. This
function calculates the storage for both the unit input (output) and the
realized input (output) environs. Realized uses the observed inputs
(outputs) rather than... | /vignettes/enaR.Rcheck/00_pkg_src/enaR/man/TES.Rd | no_license | STecchio/enaR | R | false | false | 1,380 | rd | \name{TES}
\alias{TES}
\title{
Calculate the total environ storage.
}
\description{
Calculates the total storage in each n input and output environs. This
function calculates the storage for both the unit input (output) and the
realized input (output) environs. Realized uses the observed inputs
(outputs) rather than... |
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