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 |
|---|---|---|---|---|---|---|---|---|---|
#The assignment is about cache the inverse of matix
#Rather than computing the inverse of the matrix its better to cache it avoid repeated computation
<<<<<<< HEAD
#The below function creates a special object matrix to cache the inverse.
=======
#The below function creates a special object matrix to cache the inverse... | /cachematrix.R | no_license | Vijay08/ProgrammingAssignment2 | R | false | false | 1,121 | r | #The assignment is about cache the inverse of matix
#Rather than computing the inverse of the matrix its better to cache it avoid repeated computation
<<<<<<< HEAD
#The below function creates a special object matrix to cache the inverse.
=======
#The below function creates a special object matrix to cache the inverse... |
# documentation separate from implementation because roxygen can't handle adding methods to another package's R6 classes
#' Create Azure Cosmos DB account
#'
#' Method for the [AzureRMR::az_resource_group] class.
#'
#' @rdname create_cosmosdb_account
#' @name create_cosmosdb_account
#' @aliases create_cosmosdb... | /R/add_methods.R | no_license | cran/AzureCosmosR | R | false | false | 7,893 | r | # documentation separate from implementation because roxygen can't handle adding methods to another package's R6 classes
#' Create Azure Cosmos DB account
#'
#' Method for the [AzureRMR::az_resource_group] class.
#'
#' @rdname create_cosmosdb_account
#' @name create_cosmosdb_account
#' @aliases create_cosmosdb... |
/MyNotes/02 - R Programming/applyFunctions.R | no_license | vitorefigenio/datasciencecoursera | R | false | false | 2,871 | r | ||
library(fgsea)
library(data.table)
library(ggplot2)
#cargo los datos
paths_data<-read.delim("~/Escritorio/WGCNA/KEGG_annotation/GMT_Files/LbrM2903_parsed.gmt",
header = F,
sep = "\t")
#selecciono los nombres
nams <- paths_data[, 1]
#eliminar la colu... | /WGCNA/GSEA.R | no_license | lalomartinez/ncRNA_leish | R | false | false | 1,404 | r | library(fgsea)
library(data.table)
library(ggplot2)
#cargo los datos
paths_data<-read.delim("~/Escritorio/WGCNA/KEGG_annotation/GMT_Files/LbrM2903_parsed.gmt",
header = F,
sep = "\t")
#selecciono los nombres
nams <- paths_data[, 1]
#eliminar la colu... |
##required libraries
library(osfr)
library(tidyverse)
library(here)
library(psych)
library(MOTE)
library(lmerTest)
library(lavaan)
library(semTools)
library(broom)
library(tidyLPA)
library(semPlot)
## reading in data
osf_retrieve_file("https://osf.io/86upq/") %>%
osf_download(overwrite = T)
survey_data <- read_csv... | /Sloan_grant/Survey/Survey_analyses.R | permissive | bgonzalezbustamante/data-science | R | false | false | 14,618 | r | ##required libraries
library(osfr)
library(tidyverse)
library(here)
library(psych)
library(MOTE)
library(lmerTest)
library(lavaan)
library(semTools)
library(broom)
library(tidyLPA)
library(semPlot)
## reading in data
osf_retrieve_file("https://osf.io/86upq/") %>%
osf_download(overwrite = T)
survey_data <- read_csv... |
#script for open jobs data profiling
library(DataExplorer)
library(data.table)
ojobs <- fread('./data/stem_edu/working/allOpenjobsParsed.csv')
introduce(ojobs)
| /src/burn_glass_validation/openjobs_profile/openjobs_profiling.R | no_license | uva-bi-sdad/stem_edu | R | false | false | 161 | r | #script for open jobs data profiling
library(DataExplorer)
library(data.table)
ojobs <- fread('./data/stem_edu/working/allOpenjobsParsed.csv')
introduce(ojobs)
|
\name{BLUP}
\alias{BLUP}
\alias{ENV}
\alias{gwnam}
\alias{mrr}
\title{
Best Linear Unbias Predictor
}
\description{
Genetic values for a given trait computed by REML.
}
\usage{
BLUP(trait="yield",family="all",env="all",dereg=FALSE,
MAF=0.05,use.check=TRUE,impute="FM",rm.rep=TRUE)
}
\arguments{
\i... | /man/BLUP.Rd | no_license | alenxav/SoyNAM | R | false | false | 3,848 | rd | \name{BLUP}
\alias{BLUP}
\alias{ENV}
\alias{gwnam}
\alias{mrr}
\title{
Best Linear Unbias Predictor
}
\description{
Genetic values for a given trait computed by REML.
}
\usage{
BLUP(trait="yield",family="all",env="all",dereg=FALSE,
MAF=0.05,use.check=TRUE,impute="FM",rm.rep=TRUE)
}
\arguments{
\i... |
testlist <- list(m = NULL, repetitions = 0L, in_m = structure(c(2.31584307392677e+77, 9.53818252170339e+295, 1.20688722640421e+146, 4.12396251261199e-221, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 3L)))
result <- do.call(CNull:::communities_individual_based_sampling... | /CNull/inst/testfiles/communities_individual_based_sampling_alpha/AFL_communities_individual_based_sampling_alpha/communities_individual_based_sampling_alpha_valgrind_files/1615778013-test.R | no_license | akhikolla/updatedatatype-list2 | R | false | false | 348 | r | testlist <- list(m = NULL, repetitions = 0L, in_m = structure(c(2.31584307392677e+77, 9.53818252170339e+295, 1.20688722640421e+146, 4.12396251261199e-221, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 3L)))
result <- do.call(CNull:::communities_individual_based_sampling... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/revalue.levels.R
\name{revalue.levels}
\alias{revalue.levels}
\alias{revalue.levels_}
\title{Revalue data frame factor levels.}
\usage{
revalue.levels(df, ...)
revalue.levels_(df, dots)
}
\arguments{
\item{df}{A data frame (or quitte object)... | /man/revalue.levels.Rd | no_license | pik-piam/quitte | R | false | true | 1,358 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/revalue.levels.R
\name{revalue.levels}
\alias{revalue.levels}
\alias{revalue.levels_}
\title{Revalue data frame factor levels.}
\usage{
revalue.levels(df, ...)
revalue.levels_(df, dots)
}
\arguments{
\item{df}{A data frame (or quitte object)... |
\name{ecospat.cv.glm}
\alias{ecospat.cv.glm}
\title{GLM Cross Validation}
\description{K-fold and leave-one-out cross validation for GLM.}
\usage{ecospat.cv.glm (glm.obj, K=10, cv.lim=10, jack.knife=FALSE)}
\arguments{
\item{glm.obj}{Any calibrated GLM object with a binomial error distribution.}
\i... | /ecospat/man/ecospat.cv.glm.Rd | no_license | lzhangss/ecospat | R | false | false | 1,862 | rd | \name{ecospat.cv.glm}
\alias{ecospat.cv.glm}
\title{GLM Cross Validation}
\description{K-fold and leave-one-out cross validation for GLM.}
\usage{ecospat.cv.glm (glm.obj, K=10, cv.lim=10, jack.knife=FALSE)}
\arguments{
\item{glm.obj}{Any calibrated GLM object with a binomial error distribution.}
\i... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/generated_client.R
\name{surveys_put_samples}
\alias{surveys_put_samples}
\title{Update a sample}
\usage{
surveys_put_samples(id, sample_table_id = NULL, server_name = NULL,
schema = NULL, table_name = NULL, unique_id = NULL, metadata = NUL... | /man/surveys_put_samples.Rd | permissive | wlattner/civis-r | R | false | true | 1,860 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/generated_client.R
\name{surveys_put_samples}
\alias{surveys_put_samples}
\title{Update a sample}
\usage{
surveys_put_samples(id, sample_table_id = NULL, server_name = NULL,
schema = NULL, table_name = NULL, unique_id = NULL, metadata = NUL... |
# Initial exploration of WHO data
# 20/12/2016
rm(list = ls())
# The data are all in tables contained in an Access .mdb file.
# To access this I will start by using ImportExport, which uses RODBC
pacman::p_load(
tidyverse,
stringr,
forcats,
ggplot2,
lattice, latticeExtra
)
# Let's start by using the ... | /script.R | no_license | JonMinton/who_data_explore | R | false | false | 4,770 | r | # Initial exploration of WHO data
# 20/12/2016
rm(list = ls())
# The data are all in tables contained in an Access .mdb file.
# To access this I will start by using ImportExport, which uses RODBC
pacman::p_load(
tidyverse,
stringr,
forcats,
ggplot2,
lattice, latticeExtra
)
# Let's start by using the ... |
#' Builds a small-world scale-free network and extracts VNs based on genes of interest
#'
#' This function calls createSWSFnetFromFile() and downstreamAnalysis(). Its a one strep function to create a scale-free small-world network, determines the 'best' network model, from which then vicinity networks (VNs) are extrac... | /src/petal/R/dataToVNs.R | no_license | ameya225/petalNet | R | false | false | 1,855 | r |
#' Builds a small-world scale-free network and extracts VNs based on genes of interest
#'
#' This function calls createSWSFnetFromFile() and downstreamAnalysis(). Its a one strep function to create a scale-free small-world network, determines the 'best' network model, from which then vicinity networks (VNs) are extrac... |
process__exists <- function(pid) {
.Call(c_processx__process_exists, pid)
}
| /R/process-helpers.R | permissive | alxsrobert/processx | R | false | false | 79 | r |
process__exists <- function(pid) {
.Call(c_processx__process_exists, pid)
}
|
library(seroincidence)
### Name: getAdditionalData
### Title: Get Additional Data
### Aliases: getAdditionalData
### ** Examples
## Not run:
##D getAdditionalData(fileName = "coxiellaIFAParams4.zip")
##D getAdditionalData(fileName = "yersiniaSSIParams4.zip")
##D getAdditionalData(fileName = "coxiellaIFAParams4.zi... | /data/genthat_extracted_code/seroincidence/examples/getAdditionalData.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 443 | r | library(seroincidence)
### Name: getAdditionalData
### Title: Get Additional Data
### Aliases: getAdditionalData
### ** Examples
## Not run:
##D getAdditionalData(fileName = "coxiellaIFAParams4.zip")
##D getAdditionalData(fileName = "yersiniaSSIParams4.zip")
##D getAdditionalData(fileName = "coxiellaIFAParams4.zi... |
trackpts_test <- function(x){
print("DIAGNOSTICS OF FILE")
print("unique tracks")
print(length(unique(x$track_fid)))
print("________________________________________")
print("INSPECT INDIVIDUAL TRACKPOINTS")
for(i in 1:max(x$track_fid)){
print(unique((x$name[x$track_fid==i]))) #number of unique tracks
... | /trackpts_test function.R | no_license | bjbarrett/lomas_gps_code | R | false | false | 1,308 | r | trackpts_test <- function(x){
print("DIAGNOSTICS OF FILE")
print("unique tracks")
print(length(unique(x$track_fid)))
print("________________________________________")
print("INSPECT INDIVIDUAL TRACKPOINTS")
for(i in 1:max(x$track_fid)){
print(unique((x$name[x$track_fid==i]))) #number of unique tracks
... |
# Note:
# This script is showing how to conduct the mutation mapping analysis for the small SNP dataset
data('gene_feature0')
data('snp_data')
mutated_gene <- annotateSNP(snp_input = snp_data, gene_feature = gene_feature0)
#-------------------------------------------------
# Mutation enrichment analysis
#------------... | /2 General steps to conduct the mutation mapping analysis using Yeastspot3D.R | permissive | hongzhonglu/Tutorial_for_Yeastspot3D | R | false | false | 2,872 | r | # Note:
# This script is showing how to conduct the mutation mapping analysis for the small SNP dataset
data('gene_feature0')
data('snp_data')
mutated_gene <- annotateSNP(snp_input = snp_data, gene_feature = gene_feature0)
#-------------------------------------------------
# Mutation enrichment analysis
#------------... |
##Please make sure the file "household_power_consumption.txt" is in your working
##directory
dataset<-read.table("household_power_consumption.txt",sep = ";",stringsAsFactors = FALSE,
skip = 66637,nrows = 2880)
names(dataset)<-strsplit("Date;Time;Global_active_power;Global_reactive_power;Voltage;Global_intensity;S... | /plot3.R | no_license | WLGCCYCC/ExData_Plotting1 | R | false | false | 895 | r | ##Please make sure the file "household_power_consumption.txt" is in your working
##directory
dataset<-read.table("household_power_consumption.txt",sep = ";",stringsAsFactors = FALSE,
skip = 66637,nrows = 2880)
names(dataset)<-strsplit("Date;Time;Global_active_power;Global_reactive_power;Voltage;Global_intensity;S... |
r=359.80
https://sandbox.dams.library.ucdavis.edu/fcrepo/rest/collection/sherry-lehmann/catalogs/d7mk5f/media/images/d7mk5f-005/svc:tesseract/full/full/359.80/default.jpg Accept:application/hocr+xml
| /ark_87287/d7mk5f/d7mk5f-005/rotated.r | permissive | ucd-library/wine-price-extraction | R | false | false | 199 | r | r=359.80
https://sandbox.dams.library.ucdavis.edu/fcrepo/rest/collection/sherry-lehmann/catalogs/d7mk5f/media/images/d7mk5f-005/svc:tesseract/full/full/359.80/default.jpg Accept:application/hocr+xml
|
## ======================================================================
## This file takes the simulated data sets, which are stored in separate
## files in folder /simParts, and runs all meta-analytic techniques on them.
## Then it saves the analyses in separate files in the /analysisParts folder.
## ===============... | /2-analysisFramework.R | permissive | kylehamilton/meta-showdown | R | false | false | 3,270 | r | ## ======================================================================
## This file takes the simulated data sets, which are stored in separate
## files in folder /simParts, and runs all meta-analytic techniques on them.
## Then it saves the analyses in separate files in the /analysisParts folder.
## ===============... |
library(glmnet)
library(ggplot2) # pour des grpahes plus jolies
df = read.csv("communities_data_R.csv", sep = ",", header = T)
# On fait du Lasso avec alpha = 1
# Une grille de lambda est automatiquement determinée, en partant du plus petit lambda, annulant tous les
# coefficients( sauf la constante), jusqu'Ã une c... | /Statistique_en_grande_dimension/Notebook/WADE_Malick_Exercice_2_Communities_and_Crime.R | no_license | Malick-W/Projets | R | false | false | 2,924 | r | library(glmnet)
library(ggplot2) # pour des grpahes plus jolies
df = read.csv("communities_data_R.csv", sep = ",", header = T)
# On fait du Lasso avec alpha = 1
# Une grille de lambda est automatiquement determinée, en partant du plus petit lambda, annulant tous les
# coefficients( sauf la constante), jusqu'Ã une c... |
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/pkg.R
\docType{package}
\name{docopt-package}
\alias{docopt-package}
\title{Docopt command line specification}
\description{
docopt helps you to define an interface for your command-line app, and
automatically generate a parser for it... | /man/docopt-package.Rd | no_license | extemporaneousb/docopt.R | R | false | false | 380 | rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/pkg.R
\docType{package}
\name{docopt-package}
\alias{docopt-package}
\title{Docopt command line specification}
\description{
docopt helps you to define an interface for your command-line app, and
automatically generate a parser for it... |
# Copyright 2011 Revolution Analytics
#
# 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://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... | /pkg/R/mapreduce.R | no_license | forschnix/rmr2 | R | false | false | 12,198 | r | # Copyright 2011 Revolution Analytics
#
# 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://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
#' @importFrom R6 R6Class
stat_four_gamete_class <- R6Class("stat_four_gamete", inherit = sumstat_class,
private = list(
population = NULL,
req_segsites = TRUE
),
public = list(
initialize = function(name, population, transformation) {
assert_that(is.numeric(population))
assert_that(length... | /coala/R/sumstat_four_gamete.R | no_license | ingted/R-Examples | R | false | false | 3,394 | r | #' @importFrom R6 R6Class
stat_four_gamete_class <- R6Class("stat_four_gamete", inherit = sumstat_class,
private = list(
population = NULL,
req_segsites = TRUE
),
public = list(
initialize = function(name, population, transformation) {
assert_that(is.numeric(population))
assert_that(length... |
#Obtaining Twitter Data using R
#1. Registering APRI using Twitter account
#https://apps.twitter.com
#2. Insert Values
api_key <-'xx'
api_secret <- 'xx'
access_token <- 'xx'
access_token_secret <-'xx'
library(twitteR)
setup_twitter_oauth(api_key,
api_secret,
access_token,
... | /RCode/Extracting Twitter Data and Analysis_for NLP.R | no_license | KIKI-C/NLP-Workshop | R | false | false | 10,800 | r | #Obtaining Twitter Data using R
#1. Registering APRI using Twitter account
#https://apps.twitter.com
#2. Insert Values
api_key <-'xx'
api_secret <- 'xx'
access_token <- 'xx'
access_token_secret <-'xx'
library(twitteR)
setup_twitter_oauth(api_key,
api_secret,
access_token,
... |
#' EuPathDB: Access EuPathDB annotations using AnnotationHub
#'
#' EuPathDB provides an R interface for retrieving annotation resources from
#' the EuPathDB databases: AmoebaDB, CryptoDB, FungiDB, GiardiaDB,
#' MicrosporidiaDB, PiroplasmaDB, PlasmoDB, ToxoDB, TrichDB, and TriTrypDB
#' using the Bioconductor AnnotationH... | /R/eupathdb.R | no_license | hupef/EuPathDB | R | false | false | 4,022 | r | #' EuPathDB: Access EuPathDB annotations using AnnotationHub
#'
#' EuPathDB provides an R interface for retrieving annotation resources from
#' the EuPathDB databases: AmoebaDB, CryptoDB, FungiDB, GiardiaDB,
#' MicrosporidiaDB, PiroplasmaDB, PlasmoDB, ToxoDB, TrichDB, and TriTrypDB
#' using the Bioconductor AnnotationH... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dendro.resample.R
\name{dendro.resample}
\alias{dendro.resample}
\title{Resampling temporal resolution of dendrometer data}
\usage{
dendro.resample(df, by, value)
}
\arguments{
\item{df}{dataframe with first column containing date and time in... | /man/dendro.resample.Rd | no_license | sugam72-os/dendRoAnalyst-1 | R | false | true | 1,010 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dendro.resample.R
\name{dendro.resample}
\alias{dendro.resample}
\title{Resampling temporal resolution of dendrometer data}
\usage{
dendro.resample(df, by, value)
}
\arguments{
\item{df}{dataframe with first column containing date and time in... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/utilities.R
\name{findQTLPeaks}
\alias{findQTLPeaks}
\title{Find QTL peaks}
\usage{
findQTLPeaks(qtls, mrk, pcutoff = 0.05, peak_sigma = 25,
peak_threshold = 1, ...)
}
\arguments{
\item{qtls}{}
}
\value{
Data Frame of peaks
}
\descr... | /man/findQTLPeaks.Rd | no_license | scalefreegan/clustQTL | R | false | false | 371 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/utilities.R
\name{findQTLPeaks}
\alias{findQTLPeaks}
\title{Find QTL peaks}
\usage{
findQTLPeaks(qtls, mrk, pcutoff = 0.05, peak_sigma = 25,
peak_threshold = 1, ...)
}
\arguments{
\item{qtls}{}
}
\value{
Data Frame of peaks
}
\descr... |
#HW 6 Kevin Niemann
setwd('C:/Users/kevin/Google Drive/datasci/HW6')
#install.packages("pls")
#install.packages("glmnet")
library(pls)
library(glmnet)
set.seed(20) # You will need to set the seed to 20 for this to work.
# Retrieve Breast Cancer Expression Data From the following Study:
#http://www.ncbi.nlm.... | /qtr2/hw6/HW6.R | no_license | kniemann/data-projects | R | false | false | 1,892 | r | #HW 6 Kevin Niemann
setwd('C:/Users/kevin/Google Drive/datasci/HW6')
#install.packages("pls")
#install.packages("glmnet")
library(pls)
library(glmnet)
set.seed(20) # You will need to set the seed to 20 for this to work.
# Retrieve Breast Cancer Expression Data From the following Study:
#http://www.ncbi.nlm.... |
# install.packages('rvest')
library(rvest)
title=read_html("http://sports.ltn.com.tw/baseball")
title=html_nodes(title,".boxTitle .listA .list_title")
title=html_text(title) # 只篩選出文字
# title=iconv(title,"UTF-8")
title
url=read_html("http://sports.ltn.com.tw/baseball")
url=html_nodes(url,".boxTitle .listA ... | /week_3/Week 3加強.R | no_license | PeterChiu1202/Politics-and-Information | R | false | false | 434 | r |
# install.packages('rvest')
library(rvest)
title=read_html("http://sports.ltn.com.tw/baseball")
title=html_nodes(title,".boxTitle .listA .list_title")
title=html_text(title) # 只篩選出文字
# title=iconv(title,"UTF-8")
title
url=read_html("http://sports.ltn.com.tw/baseball")
url=html_nodes(url,".boxTitle .listA ... |
#' @export
print.json <- function( x, ... ) cat( x )
#' @export
print.ndjson <- function( x, ... ) cat( x )
#' Pretty Json
#'
#' Adds indentiation to a JSON string
#'
#' @param json string of JSON
#' @param ... other argments passed to \link{to_json}
#'
#' @examples
#'
#' df <- data.frame(id = 1:10, val = rnorm(... | /R/pretty.R | permissive | SymbolixAU/jsonify | R | false | false | 1,419 | r |
#' @export
print.json <- function( x, ... ) cat( x )
#' @export
print.ndjson <- function( x, ... ) cat( x )
#' Pretty Json
#'
#' Adds indentiation to a JSON string
#'
#' @param json string of JSON
#' @param ... other argments passed to \link{to_json}
#'
#' @examples
#'
#' df <- data.frame(id = 1:10, val = rnorm(... |
##' QGIS Algorithm provided by QGIS (native c++) Extract M values (native:extractmvalues)
##'
##' @title QGIS algorithm Extract M values
##'
##' @param INPUT `source` - Input layer. Path to a vector layer.
##' @param SUMMARIES `enum` of `("First", "Last", "Count", "Sum", "Mean", "Median", "St dev (pop)", "Minimum", "M... | /R/qgis_extractmvalues.R | permissive | VB6Hobbyst7/r_package_qgis | R | false | false | 1,691 | r | ##' QGIS Algorithm provided by QGIS (native c++) Extract M values (native:extractmvalues)
##'
##' @title QGIS algorithm Extract M values
##'
##' @param INPUT `source` - Input layer. Path to a vector layer.
##' @param SUMMARIES `enum` of `("First", "Last", "Count", "Sum", "Mean", "Median", "St dev (pop)", "Minimum", "M... |
# Copyright 2015 Morningstar, Inc.
#library(xlsx)
#library(gdata)
library(XLConnect)
library(ggplot2)
# RBSA methodology https://corporate.morningstar.com/ib/documents/MethodologyDocuments/IBBAssociates/ReturnsBasedAnalysis.pdf
# data dump from PresentationStudio
ds<-(function(){
xlsFile<-"OE Equity 1 - RBSA_20141... | /rbsa.R | no_license | racoon971/dss.Morningstar.RBSA | R | false | false | 3,585 | r | # Copyright 2015 Morningstar, Inc.
#library(xlsx)
#library(gdata)
library(XLConnect)
library(ggplot2)
# RBSA methodology https://corporate.morningstar.com/ib/documents/MethodologyDocuments/IBBAssociates/ReturnsBasedAnalysis.pdf
# data dump from PresentationStudio
ds<-(function(){
xlsFile<-"OE Equity 1 - RBSA_20141... |
## R
# https://stackoverflow.com/questions/25136059/how-to-show-working-directory-in-r-prompt
myRPrompt <- function(...) {
verbose <- F
p <- getwd() # absolute path as pwd
if (verbose) message("getwd(): ", getwd())
#home <- regexpr(path.expand("~"), p)
home <- regexpr(system("readlink -f ~", inter... | /myRPrompt.r | no_license | chrisdane/functions | R | false | false | 2,149 | r | ## R
# https://stackoverflow.com/questions/25136059/how-to-show-working-directory-in-r-prompt
myRPrompt <- function(...) {
verbose <- F
p <- getwd() # absolute path as pwd
if (verbose) message("getwd(): ", getwd())
#home <- regexpr(path.expand("~"), p)
home <- regexpr(system("readlink -f ~", inter... |
\name{rlmDD}
\alias{rlmDD}
\title{
Data driven robust methods
}
\description{
Robust estimation often relies on a dispersion function that is more slowly varying at large values than the squared function. However, the choice of tuning constant in dispersion
function may impact the estimation efficiency to a great exte... | /man/rlmDD.Rd | no_license | e-123456/rlmDataDriven | R | false | false | 3,291 | rd | \name{rlmDD}
\alias{rlmDD}
\title{
Data driven robust methods
}
\description{
Robust estimation often relies on a dispersion function that is more slowly varying at large values than the squared function. However, the choice of tuning constant in dispersion
function may impact the estimation efficiency to a great exte... |
testlist <- list(A = structure(c(3.1838324823962e-313, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = 5:6), left = 0L, right = 0L, x = numeric(0))
result <- do.call(mgss:::MVP_normalfactor_rcpp,testlist)
str(result) | /mgss/inst/testfiles/MVP_normalfactor_rcpp/AFL_MVP_normalfactor_rcpp/MVP_normalfactor_rcpp_valgrind_files/1615948858-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 265 | r | testlist <- list(A = structure(c(3.1838324823962e-313, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = 5:6), left = 0L, right = 0L, x = numeric(0))
result <- do.call(mgss:::MVP_normalfactor_rcpp,testlist)
str(result) |
testlist <- list(ends = c(-1125300777L, 765849512L, -1760774663L, 791623263L, 1358782356L, -128659642L, -14914341L, 1092032927L, 1837701012L, 1632068659L), pts = c(1758370433L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,... | /IntervalSurgeon/inst/testfiles/rcpp_pile/AFL_rcpp_pile/rcpp_pile_valgrind_files/1609874808-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 729 | r | testlist <- list(ends = c(-1125300777L, 765849512L, -1760774663L, 791623263L, 1358782356L, -128659642L, -14914341L, 1092032927L, 1837701012L, 1632068659L), pts = c(1758370433L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,... |
#### Preamble ####
# Purpose: Prepare and clean the survey data downloaded from IPUMS USA 2018 5-years ACS.
# Author: Hanrui Dou, Hanjing Huang, Hairuo Wang, Xuan Zhong - Group 161
# Data: 2 Nomverber 2020
# Contact: hairuo.wang@mail.utoronto.ca, dhr1142638924@gmail.com, hanjing.huang@mail.utoronto.ca, xuan.zhong@mail... | /01-data_cleaning-post-strat1.R | no_license | HairuoWang/STA304-PS3-G161 | R | false | false | 2,202 | r | #### Preamble ####
# Purpose: Prepare and clean the survey data downloaded from IPUMS USA 2018 5-years ACS.
# Author: Hanrui Dou, Hanjing Huang, Hairuo Wang, Xuan Zhong - Group 161
# Data: 2 Nomverber 2020
# Contact: hairuo.wang@mail.utoronto.ca, dhr1142638924@gmail.com, hanjing.huang@mail.utoronto.ca, xuan.zhong@mail... |
stateplane2latlon <- function(X, Y, metric=TRUE){
# latlon <- data.table(longitude = c(1148703.5804669, 1148721.69534794,
# 1148718.58006945, 1148719.92031838,
# 1148722.28519294),
# latitude = c(1938916.1610564... | /west-nile-virus-predictions/R/functions/stateplane2latlon.R | no_license | mohcinemadkour/west-nile-virus-predictions | R | false | false | 1,802 | r |
stateplane2latlon <- function(X, Y, metric=TRUE){
# latlon <- data.table(longitude = c(1148703.5804669, 1148721.69534794,
# 1148718.58006945, 1148719.92031838,
# 1148722.28519294),
# latitude = c(1938916.1610564... |
#' @title FUNCTION_TITLE
#' @description FUNCTION_DESCRIPTION
#' @param draw_level_cell_pred PARAM_DESCRIPTION
#' @param mask PARAM_DESCRIPTION, Default: simple_raster
#' @param return_as_raster PARAM_DESCRIPTION, Default: TRUE
#' @param summary_stat PARAM_DESCRIPTION, Default: 'mean'
#' @param ... PARAM_DESCRIPTION
#... | /antibiotic_usage/mbg_central/LBDCore/R/make_cell_pred_summary.R | no_license | The-Oxford-GBD-group/antibiotic_modelling_code | R | false | false | 1,691 | r |
#' @title FUNCTION_TITLE
#' @description FUNCTION_DESCRIPTION
#' @param draw_level_cell_pred PARAM_DESCRIPTION
#' @param mask PARAM_DESCRIPTION, Default: simple_raster
#' @param return_as_raster PARAM_DESCRIPTION, Default: TRUE
#' @param summary_stat PARAM_DESCRIPTION, Default: 'mean'
#' @param ... PARAM_DESCRIPTION
#... |
#'
#' This function allows you to calculate an average expression for the list of genes of your interest.
#'
#' @param Seurat_obj Seurat: your Seurat object
#' @param genesets, list: named list with genesets
#' @param reset_genesets, bool: if you want reset already existing genesets with a new assay object
#'
#' @retur... | /R/quantify_genesets.R | no_license | GrigoriiNos/rimmi.rnaseq | R | false | false | 1,580 | r | #'
#' This function allows you to calculate an average expression for the list of genes of your interest.
#'
#' @param Seurat_obj Seurat: your Seurat object
#' @param genesets, list: named list with genesets
#' @param reset_genesets, bool: if you want reset already existing genesets with a new assay object
#'
#' @retur... |
library("reshape2")
## Read Data
subject_test <- read.table("UCI HAR Dataset/test/subject_test.txt")
subject_train <- read.table("UCI HAR Dataset/train/subject_train.txt")
X_test <- read.table("UCI HAR Dataset/test/X_test.txt")
X_train <- read.table("UCI HAR Dataset/train/X_train.txt")
y_test <- read.table("UCI HAR Dat... | /run_analysis.R | no_license | tmpusr1/getcleandataproject | R | false | false | 2,295 | r | library("reshape2")
## Read Data
subject_test <- read.table("UCI HAR Dataset/test/subject_test.txt")
subject_train <- read.table("UCI HAR Dataset/train/subject_train.txt")
X_test <- read.table("UCI HAR Dataset/test/X_test.txt")
X_train <- read.table("UCI HAR Dataset/train/X_train.txt")
y_test <- read.table("UCI HAR Dat... |
#########################################################
#03 week 1 assignment
# April 26. 2014, Rae Woong Park
#########################################################
library(data.table)
#setwd("C:/Users/Administrator/Documents/GitHub/GettingandCleaningData/")
#setwd("C:/Users/Administrator/Documents/data/UCI HAR ... | /run_analysis.R | no_license | rwpark99/GettingandCleaningData | R | false | false | 3,094 | r | #########################################################
#03 week 1 assignment
# April 26. 2014, Rae Woong Park
#########################################################
library(data.table)
#setwd("C:/Users/Administrator/Documents/GitHub/GettingandCleaningData/")
#setwd("C:/Users/Administrator/Documents/data/UCI HAR ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/psr.R
\docType{package}
\name{psr}
\alias{psr}
\title{psr}
\description{
A package for computing various measures relating to reliability of performance science metrics. It
contains functions to compute the Typical Error (TE), Coefficient o... | /man/psr.Rd | permissive | tommy-mcginn/psr | R | false | true | 523 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/psr.R
\docType{package}
\name{psr}
\alias{psr}
\title{psr}
\description{
A package for computing various measures relating to reliability of performance science metrics. It
contains functions to compute the Typical Error (TE), Coefficient o... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/stach_extensions.R
\docType{class}
\name{StachExtensions}
\alias{StachExtensions}
\title{StachExtensions}
\format{
An \code{R6Class} generator object
}
\description{
The purpose of this class is to provide the helper methods for converting st... | /auto-generated-sdk/man/StachExtensions.Rd | permissive | afernandes85/analyticsapi-engines-r-sdk | R | false | true | 1,676 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/stach_extensions.R
\docType{class}
\name{StachExtensions}
\alias{StachExtensions}
\title{StachExtensions}
\format{
An \code{R6Class} generator object
}
\description{
The purpose of this class is to provide the helper methods for converting st... |
#:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "fri_c1_1000_25")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "binaryClass")
lrn = ma... | /models/openml_fri_c1_1000_25/classification_binaryClass/e1b7376588a14612daafe09b4bf0fbf4/code.R | no_license | pysiakk/CaseStudies2019S | R | false | false | 691 | r | #:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "fri_c1_1000_25")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "binaryClass")
lrn = ma... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ConstraintTaxo2newick.R
\name{ConstraintTaxo2newick}
\alias{ConstraintTaxo2newick}
\title{Build a multifurcating topological constraint tree for RAxML}
\usage{
ConstraintTaxo2newick(
inputTaxo = NULL,
Taxo.Hier = "Phylum2Genus",
inputCo... | /man/ConstraintTaxo2newick.Rd | no_license | dvdeme/regPhylo | R | false | true | 4,829 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ConstraintTaxo2newick.R
\name{ConstraintTaxo2newick}
\alias{ConstraintTaxo2newick}
\title{Build a multifurcating topological constraint tree for RAxML}
\usage{
ConstraintTaxo2newick(
inputTaxo = NULL,
Taxo.Hier = "Phylum2Genus",
inputCo... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_credibility_trends.R
\name{get_credibility_trends}
\alias{get_credibility_trends}
\title{Get data credibility and trends from the BBS analysis results}
\usage{
get_credibility_trends(url = "https://www.mbr-pwrc.usgs.gov/cgi-bin/atlasa1... | /man/get_credibility_trends.Rd | permissive | ethanwhite/bbsAssistant | R | false | true | 869 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_credibility_trends.R
\name{get_credibility_trends}
\alias{get_credibility_trends}
\title{Get data credibility and trends from the BBS analysis results}
\usage{
get_credibility_trends(url = "https://www.mbr-pwrc.usgs.gov/cgi-bin/atlasa1... |
#' Creates bootstrap samples of the parameters
#'
#' \code{parbootstrap} creates bootstrap samples of the parameters.
#' @param qp output from quickpsy
#' @export
parbootstrap <- function(qp) {
if (qp$pariniset) {
if (is.atomic(parini)) {
parini <- qp$par
pariniset <- FALSE
}
else{
parin... | /R/parbootstrap.R | no_license | cran/quickpsy | R | false | false | 807 | r | #' Creates bootstrap samples of the parameters
#'
#' \code{parbootstrap} creates bootstrap samples of the parameters.
#' @param qp output from quickpsy
#' @export
parbootstrap <- function(qp) {
if (qp$pariniset) {
if (is.atomic(parini)) {
parini <- qp$par
pariniset <- FALSE
}
else{
parin... |
## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
makeCacheMatrix <- function(x = matrix()) {
## Initilize the result vector
inv <- NULL
## Set the value of the Cache Matrix
set <- function(y) {
x <<- y
... | /cachematrix.R | no_license | thxthn/ProgrammingAssignment2 | R | false | false | 1,208 | r | ## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
makeCacheMatrix <- function(x = matrix()) {
## Initilize the result vector
inv <- NULL
## Set the value of the Cache Matrix
set <- function(y) {
x <<- y
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/flextable_sizes.R
\name{height}
\alias{height}
\alias{height_all}
\title{Set flextable rows height}
\usage{
height(x, i = NULL, height, part = "body")
height_all(x, height, part = "all")
}
\arguments{
\item{x}{flextable object}
\item{i}{row... | /man/height.Rd | no_license | pvictor/flextable | R | false | true | 980 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/flextable_sizes.R
\name{height}
\alias{height}
\alias{height_all}
\title{Set flextable rows height}
\usage{
height(x, i = NULL, height, part = "body")
height_all(x, height, part = "all")
}
\arguments{
\item{x}{flextable object}
\item{i}{row... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/options.R
\name{sass_options}
\alias{sass_options}
\title{Compiler Options for Sass}
\usage{
sass_options(precision = 5, output_style = "expanded",
indented_syntax = FALSE, include_path = "",
source_comments = FALSE, indent_type = "space"... | /man/sass_options.Rd | permissive | schloerke/sass | R | false | true | 2,453 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/options.R
\name{sass_options}
\alias{sass_options}
\title{Compiler Options for Sass}
\usage{
sass_options(precision = 5, output_style = "expanded",
indented_syntax = FALSE, include_path = "",
source_comments = FALSE, indent_type = "space"... |
alphabet <-
function(n) {
letters <- c("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z")
sample(letters, n, replace = T)
}
| /R/alphabet.R | no_license | dtreisman/Alphabet | R | false | false | 213 | r | alphabet <-
function(n) {
letters <- c("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z")
sample(letters, n, replace = T)
}
|
testlist <- list(f = structure(c(9.41578138663341e-290, 1.56770832976572e-142, 1.55224558988362e-270, 1.51948358578169e-262, 6.52422101813805e+104, 2.82187483866939e-13, 5.84306544121847e-111, 2.30980258295413e-182, 7.7138684480244e+222, 7.63196218141027e-179, 1.5169999407476e-149, 8.84503376600421e+276, 8.24884434... | /issuestests/icosa/inst/testfiles/xxxxyyyyzzzz_/xxxxyyyyzzzz__output/log_d54768b7cb0aa48ca59c3cb777a9613367bd064c/xxxxyyyyzzzz_-test.R | no_license | akhikolla/RcppDeepStateTest | R | false | false | 2,472 | r | testlist <- list(f = structure(c(9.41578138663341e-290, 1.56770832976572e-142, 1.55224558988362e-270, 1.51948358578169e-262, 6.52422101813805e+104, 2.82187483866939e-13, 5.84306544121847e-111, 2.30980258295413e-182, 7.7138684480244e+222, 7.63196218141027e-179, 1.5169999407476e-149, 8.84503376600421e+276, 8.24884434... |
# evaluate xgboost on benchmark datasets
rm(list=ls())
options(scipen = 999)
rerfPath <- "~/work/tyler/"
dataPath <- "~/work/tyler/Data/uci/processed/"
library(xgboost)
library(caret)
library(plyr)
source(paste0(rerfPath, "RandomerForest/R/Code/Utils/GetFolds.R"))
testError <- list()
colSample <- list()
dataSet <- ... | /R/Code/Experiments/2018.01.31/task19.R | no_license | shlpu/RandomerForest | R | false | false | 3,622 | r | # evaluate xgboost on benchmark datasets
rm(list=ls())
options(scipen = 999)
rerfPath <- "~/work/tyler/"
dataPath <- "~/work/tyler/Data/uci/processed/"
library(xgboost)
library(caret)
library(plyr)
source(paste0(rerfPath, "RandomerForest/R/Code/Utils/GetFolds.R"))
testError <- list()
colSample <- list()
dataSet <- ... |
\name{dm2.refGene.LENGTH}
\docType{data}
\alias{dm2.refGene.LENGTH}
\title{Transcript length data for the organism dm}
\description{dm2.refGene.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 between a gene ID and it... | /man/dm2.refGene.LENGTH.Rd | no_license | nadiadavidson/geneLenDataBase | R | false | false | 717 | rd | \name{dm2.refGene.LENGTH}
\docType{data}
\alias{dm2.refGene.LENGTH}
\title{Transcript length data for the organism dm}
\description{dm2.refGene.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 between a gene ID and it... |
#scoringKey.R
#Author: Morgan Strom
#Date: 18-08-2015
#Function to create scoring key from dataframe with scoring key
#Input:
#Data frame "key.df" containing item ID and keys
#(Name of Item ID column = "id", Key column = "key")
#Output:
#List containing scoring key
scoringKey <- function(key.df) {
#Make sure that t... | /R/scoringKey.R | no_license | talentlens/talentlens | R | false | false | 1,131 | r | #scoringKey.R
#Author: Morgan Strom
#Date: 18-08-2015
#Function to create scoring key from dataframe with scoring key
#Input:
#Data frame "key.df" containing item ID and keys
#(Name of Item ID column = "id", Key column = "key")
#Output:
#List containing scoring key
scoringKey <- function(key.df) {
#Make sure that t... |
library('dplyr')
library('stringr')
library('ggplot2')
files <- list.files('/home/piotr/Uczelnia/PracaMagisterska/Dane/train')
setwd('/home/piotr/Uczelnia/PracaMagisterska/Dane/train')
files <- data.frame(filename=files, stringsAsFactors = FALSE)
label_files <- files %>% filter(str_detect(filename, 'label'))
df_list <-... | /analysis.R | no_license | plubon/Basecaller | R | false | false | 780 | r | library('dplyr')
library('stringr')
library('ggplot2')
files <- list.files('/home/piotr/Uczelnia/PracaMagisterska/Dane/train')
setwd('/home/piotr/Uczelnia/PracaMagisterska/Dane/train')
files <- data.frame(filename=files, stringsAsFactors = FALSE)
label_files <- files %>% filter(str_detect(filename, 'label'))
df_list <-... |
count <- 0
for(i in 1:9){
row_r <- table(Solution[i,])
count <- count + sum(row_r - 1)
}
for(j in 1:9){
col_r <- table(Solution[,j])
count <- count + sum(col_r - 1)
} | /test.R | no_license | Karl1992/Soduku-by-R | R | false | false | 174 | r | count <- 0
for(i in 1:9){
row_r <- table(Solution[i,])
count <- count + sum(row_r - 1)
}
for(j in 1:9){
col_r <- table(Solution[,j])
count <- count + sum(col_r - 1)
} |
MultiCompLineups = function (username, password, competitionmatrix, version = "v4",
baseurl = "https://data.statsbomb.com/api/", parallel = TRUE,
cores = detectCores())
{
events <- tibble()
for (i in 1:dim(competitionmatrix)[1]) {
temp.lineups <- tibble()
competition_id <- as.numeric(... | /R/MultiCompLineups.R | no_license | statsbomb/StatsBombR | R | false | false | 711 | r | MultiCompLineups = function (username, password, competitionmatrix, version = "v4",
baseurl = "https://data.statsbomb.com/api/", parallel = TRUE,
cores = detectCores())
{
events <- tibble()
for (i in 1:dim(competitionmatrix)[1]) {
temp.lineups <- tibble()
competition_id <- as.numeric(... |
install.packages("tidyverse")
library(tidyverse)
library(dplyr)
demo_table1 <- read.csv(file='MechaCar_mpg.csv',check.names=F,stringsAsFactors = F)
linear_regression <- lm(mpg ~ vehicle_length + vehicle_weight + spoiler_angle + ground_clearance + AWD,data=demo_table1)#generate multiple linear regression model
summar... | /MechaCarChallenge.RScript.R | no_license | worksm/MechaCar_Statistical_Analysis | R | false | false | 995 | r | install.packages("tidyverse")
library(tidyverse)
library(dplyr)
demo_table1 <- read.csv(file='MechaCar_mpg.csv',check.names=F,stringsAsFactors = F)
linear_regression <- lm(mpg ~ vehicle_length + vehicle_weight + spoiler_angle + ground_clearance + AWD,data=demo_table1)#generate multiple linear regression model
summar... |
consumption <- read.csv("C:/Users/Erick/Downloads/household_power_consumption.txt", sep=";", na.strings="?",stringsAsFactors = FALSE)
consumption$DateTime<-strptime(paste(consumption$Date,consumption$Time),'%d/%m/%Y %H:%M:%S')
studied_consumption<-subset(consumption,DateTime>=strptime('2007-02-01','%Y-%m-%d') & DateT... | /plot1.R | no_license | ErickDany/ExData_Plotting1 | R | false | false | 541 | r | consumption <- read.csv("C:/Users/Erick/Downloads/household_power_consumption.txt", sep=";", na.strings="?",stringsAsFactors = FALSE)
consumption$DateTime<-strptime(paste(consumption$Date,consumption$Time),'%d/%m/%Y %H:%M:%S')
studied_consumption<-subset(consumption,DateTime>=strptime('2007-02-01','%Y-%m-%d') & DateT... |
\name{gmB}
\alias{gmB}
\docType{data}
\title{Graphical Model 5-Dim Binary Example Data}
\description{
This data set contains a matrix containing information on five binary
variables (coded as 0/1) and the corresonding DAG model.
}
\usage{data(gmB)}
\format{
The format is a list of two components
\describe{
\ite... | /man/gmB.Rd | no_license | cran/pcalg | R | false | false | 1,148 | rd | \name{gmB}
\alias{gmB}
\docType{data}
\title{Graphical Model 5-Dim Binary Example Data}
\description{
This data set contains a matrix containing information on five binary
variables (coded as 0/1) and the corresonding DAG model.
}
\usage{data(gmB)}
\format{
The format is a list of two components
\describe{
\ite... |
require(shiny)
require(shinythemes)
require(shinydashboard)
require(DT)
require(htmlwidgets)
require(sparkline) #AWS has the latest github version
suppressPackageStartupMessages(require(googleVis))
source("sparkline.R")
shinyUI( dashboardPage(
#fluidPage(theme = shinytheme("united"),
skin="yellow",
dashboardH... | /models/maps/ui.R | no_license | yenlow/NextBestStore | R | false | false | 2,890 | r | require(shiny)
require(shinythemes)
require(shinydashboard)
require(DT)
require(htmlwidgets)
require(sparkline) #AWS has the latest github version
suppressPackageStartupMessages(require(googleVis))
source("sparkline.R")
shinyUI( dashboardPage(
#fluidPage(theme = shinytheme("united"),
skin="yellow",
dashboardH... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/algorithms.R
\name{Be16NDTIblue}
\alias{Be16NDTIblue}
\title{Be16NDTIblue algorithm}
\usage{
Be16NDTIblue(w658, w458)
}
\arguments{
\item{w658}{numeric. Value at wavelength of 658 nm}
\item{w458}{numeric. Value at wavelength of 458 nm}
}
\va... | /man/Be16NDTIblue.Rd | permissive | RAJohansen/waterquality | R | false | true | 3,015 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/algorithms.R
\name{Be16NDTIblue}
\alias{Be16NDTIblue}
\title{Be16NDTIblue algorithm}
\usage{
Be16NDTIblue(w658, w458)
}
\arguments{
\item{w658}{numeric. Value at wavelength of 658 nm}
\item{w458}{numeric. Value at wavelength of 458 nm}
}
\va... |
#!/usr/bin/env Rscript
library(LTN)
argv=commandArgs(TRUE)
WORK_DIR=argv[1]
#source(paste0(WORK_DIR,"/src/utility/utility.R"))
#source(paste0(WORK_DIR,"/src/utility/mixed_effects.R"))
niter=as.numeric(argv[2])
covariate_index=as.numeric(argv[3])
#model_index=as.numeric(argv[4])
model_index=2
#lambda=as.numeric(argv[5]... | /src/application/application.R | no_license | ZhuoqunWang0120/LTN_analysis-JASA_1st_submission | R | false | false | 2,387 | r | #!/usr/bin/env Rscript
library(LTN)
argv=commandArgs(TRUE)
WORK_DIR=argv[1]
#source(paste0(WORK_DIR,"/src/utility/utility.R"))
#source(paste0(WORK_DIR,"/src/utility/mixed_effects.R"))
niter=as.numeric(argv[2])
covariate_index=as.numeric(argv[3])
#model_index=as.numeric(argv[4])
model_index=2
#lambda=as.numeric(argv[5]... |
library(readxl)
library(zoo)
library(openxlsx)
library(forecast)
library(lmtest)
library(tseries)
library(ggplot2)
library(scales)
library(psych)
# Functions ----------------------------
mutate_data <- function(df) {
dn <- ts(df, start = c(1996), frequency = 1)
dnt <- window(dn, end = 2019)
return(da... | /analysis.R | permissive | FunnyRabbitIsAHabbit/UniProject | R | false | false | 7,578 | r | library(readxl)
library(zoo)
library(openxlsx)
library(forecast)
library(lmtest)
library(tseries)
library(ggplot2)
library(scales)
library(psych)
# Functions ----------------------------
mutate_data <- function(df) {
dn <- ts(df, start = c(1996), frequency = 1)
dnt <- window(dn, end = 2019)
return(da... |
# install.packages('keras')
# install.packages('purrr')
# install.packages('functional')
library(IsolationForest)
library(MASS)
library(caret)
library(fGarch)
library(fitdistrplus)
library(pracma)
library(BBmisc)
library(functional)
library(dplyr)
library(keras)
library(lubridate)
library(tensorflow)
Sys.sleep(5)
insta... | /bs2/Model2_creditcard.R | no_license | paai-lab/Online-Anomaly-Detection-Extension-2021 | R | false | false | 16,338 | r | # install.packages('keras')
# install.packages('purrr')
# install.packages('functional')
library(IsolationForest)
library(MASS)
library(caret)
library(fGarch)
library(fitdistrplus)
library(pracma)
library(BBmisc)
library(functional)
library(dplyr)
library(keras)
library(lubridate)
library(tensorflow)
Sys.sleep(5)
insta... |
##plot1
## Read data from file:
hpc <- read.csv("~/household_power_consumption.txt", sep=";")
## Subset required data (only two dates):
hpc2 <- subset(hpc, Date == "1/2/2007" | Date == "2/2/2007")
## Convert date and time formats:
hpc3 <- transform(hpc2, Date = as.Date(hpc2$Date, format = "%d/%m/%Y"))
hpc4 <- transform... | /plot1.R | no_license | pinakmishra/ExData_Plotting1 | R | false | false | 779 | r | ##plot1
## Read data from file:
hpc <- read.csv("~/household_power_consumption.txt", sep=";")
## Subset required data (only two dates):
hpc2 <- subset(hpc, Date == "1/2/2007" | Date == "2/2/2007")
## Convert date and time formats:
hpc3 <- transform(hpc2, Date = as.Date(hpc2$Date, format = "%d/%m/%Y"))
hpc4 <- transform... |
#' Space headway \code{h} between the lead and following vehicles at time \code{t}. Lead and following vehicles use \code{gbm} and constant speed models, respectively.
#'
#' @param xl0 location of lead vehicle at \code{t} = 0, a number
#' @param ul0 pre-breakdown speed of lead vehicle, a number
#' @param theta a \code{... | /R/f1.R | permissive | PJOssenbruggen/Basic | R | false | false | 749 | r | #' Space headway \code{h} between the lead and following vehicles at time \code{t}. Lead and following vehicles use \code{gbm} and constant speed models, respectively.
#'
#' @param xl0 location of lead vehicle at \code{t} = 0, a number
#' @param ul0 pre-breakdown speed of lead vehicle, a number
#' @param theta a \code{... |
#-------------------------------------------server.R -----------------------------------------#
# Ce fichier contient lest le coeur de l'application. il est le backend de l'application. Il #
# reçoit les requetes de l'interface, les traitent, et les renvoie à l'interface pour les #
# afficher.Les variables de... | /server.R | no_license | yamess/R-shiny-Dashboard | R | false | false | 9,197 | r |
#-------------------------------------------server.R -----------------------------------------#
# Ce fichier contient lest le coeur de l'application. il est le backend de l'application. Il #
# reçoit les requetes de l'interface, les traitent, et les renvoie à l'interface pour les #
# afficher.Les variables de... |
#' ChainNetwork
#'
#' Spawn a chain network covariance matrix
#'
#' @param p Positive integer.The desired number of dimensions.
#' @param n_perm Positive integer. The first n_perm dimensions will be permuted randomly.
#' @param a Positive float between 0 and 1. Scale parameter for the elements of the covariance matrix
... | /R/models.R | no_license | lorenzha/hdcd | R | false | false | 6,537 | r | #' ChainNetwork
#'
#' Spawn a chain network covariance matrix
#'
#' @param p Positive integer.The desired number of dimensions.
#' @param n_perm Positive integer. The first n_perm dimensions will be permuted randomly.
#' @param a Positive float between 0 and 1. Scale parameter for the elements of the covariance matrix
... |
# ==============================================================================
# Functions for getting and setting DEFAULT values for visual properties,
# organized into sections:
#
# I. General functions for setting node, edge and network defaults
# II. Specific functions for setting particular node, edge and networ... | /R/StyleDefaults.R | permissive | kozo2/RCy3 | R | false | false | 61,937 | r | # ==============================================================================
# Functions for getting and setting DEFAULT values for visual properties,
# organized into sections:
#
# I. General functions for setting node, edge and network defaults
# II. Specific functions for setting particular node, edge and networ... |
# Number of splits (copy from above)
ksplits = ksplits
# Initialize empty lists
modell = list()
modell.predict = list()
modell.predict.p = list()
history = list()
# Loop over k-folds
for (fold in 1:ksplits) {
cat('Fold: ' ,fold, '\n')
# extract indices for fold
ix.test <- as.numeric(unlist(lapply(xv.kfold, fu... | /R/NN_fitGenerator_2hidden_64-32nodes.R | permissive | passt/bloodinthedish | R | false | false | 2,293 | r |
# Number of splits (copy from above)
ksplits = ksplits
# Initialize empty lists
modell = list()
modell.predict = list()
modell.predict.p = list()
history = list()
# Loop over k-folds
for (fold in 1:ksplits) {
cat('Fold: ' ,fold, '\n')
# extract indices for fold
ix.test <- as.numeric(unlist(lapply(xv.kfold, fu... |
# not exported
reconstruct.vector<-function(x,index,n)
{
if(length(x) == n+1) { return(x) }
y<-rep(NA,n+1)
y[1]=x[1]
y[index+1]=x[-1]
##deal with start
i=1
while(is.na(y[i+1])) i=i+1
# if(i<n) y[2:(i+1)]=0
if(i<n) y[2:(i+1)]=x[2]
for(i in 2:n){
if(is.na(y[i+1])) y[i+1]=y[i]
}
... | /fuzzedpackages/changepoint.mv/R/mrc.R | no_license | akhikolla/testpackages | R | false | false | 7,855 | r |
# not exported
reconstruct.vector<-function(x,index,n)
{
if(length(x) == n+1) { return(x) }
y<-rep(NA,n+1)
y[1]=x[1]
y[index+1]=x[-1]
##deal with start
i=1
while(is.na(y[i+1])) i=i+1
# if(i<n) y[2:(i+1)]=0
if(i<n) y[2:(i+1)]=x[2]
for(i in 2:n){
if(is.na(y[i+1])) y[i+1]=y[i]
}
... |
library(lingtypology)
x <- read.csv("strange.csv", sep = ";", header = TRUE, encoding = "UTF-8")
map.feature(languages = x$language,
features = x$language,
title = "Languages",
stroke.features = x$strange,
stroke.title = "Strange nasals",
popup = x$bibl... | /mapafrica_strange_nasals.R | no_license | sudarikova/cartography | R | false | false | 529 | r | library(lingtypology)
x <- read.csv("strange.csv", sep = ";", header = TRUE, encoding = "UTF-8")
map.feature(languages = x$language,
features = x$language,
title = "Languages",
stroke.features = x$strange,
stroke.title = "Strange nasals",
popup = x$bibl... |
# This script is used to make an entry on the kaggle Titanic dataset
#packages: caret, randomForest
# I also prefer the tidyverse set of packages for any data wrangling I need
#to see EDA for the Titanic dataset look at the titanic_EDA upload
library(caret)
library(randomForest)
library(tidyverse)
train<- read.csv("/... | /titanic_prediction_script.R | no_license | Holt-Williams/Titanic_Kaggle | R | false | false | 2,455 | r | # This script is used to make an entry on the kaggle Titanic dataset
#packages: caret, randomForest
# I also prefer the tidyverse set of packages for any data wrangling I need
#to see EDA for the Titanic dataset look at the titanic_EDA upload
library(caret)
library(randomForest)
library(tidyverse)
train<- read.csv("/... |
#########################################
#
# R code for generating simulated
# TTE data using numerical integration
# of hazard in R.
#
#########################################
library(mrgsolve)
library(dplyr)
library(multidplyr)
library(readr)
library(XML)
#library(flexsurv)
library(survival)
library(survminer)
#'... | /final_mod/mrgsolveVPC_finalModel.r | no_license | frenchjl/TTEmanuscript | R | false | false | 5,451 | r | #########################################
#
# R code for generating simulated
# TTE data using numerical integration
# of hazard in R.
#
#########################################
library(mrgsolve)
library(dplyr)
library(multidplyr)
library(readr)
library(XML)
#library(flexsurv)
library(survival)
library(survminer)
#'... |
% Generated by roxygen2 (4.0.1): do not edit by hand
\name{load.trees}
\alias{load.trees}
\title{Custom functions to load tree lists so that rwty can do basic processing on the way in.}
\usage{
load.trees(file, type = "nexus", gens.per.tree = NA, trim = 1,
skiplines.p = 1)
}
\arguments{
\item{file}{A path to a .t fil... | /rwty/man/load.trees.Rd | no_license | jamiepg1/RWTY | R | false | false | 1,333 | rd | % Generated by roxygen2 (4.0.1): do not edit by hand
\name{load.trees}
\alias{load.trees}
\title{Custom functions to load tree lists so that rwty can do basic processing on the way in.}
\usage{
load.trees(file, type = "nexus", gens.per.tree = NA, trim = 1,
skiplines.p = 1)
}
\arguments{
\item{file}{A path to a .t fil... |
library(BayesDA)
### Name: cow
### Title: Data from an Experiment with Treatment Assignment Based on
### Covariates
### Aliases: cow
### Keywords: datasets
### ** Examples
data(cow)
summary(cow)
names(cow)
# Investigating balance on pretreatment variables:
with(cow, tapply(lactation, level, mean))
with(cow, tappl... | /data/genthat_extracted_code/BayesDA/examples/cow.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 344 | r | library(BayesDA)
### Name: cow
### Title: Data from an Experiment with Treatment Assignment Based on
### Covariates
### Aliases: cow
### Keywords: datasets
### ** Examples
data(cow)
summary(cow)
names(cow)
# Investigating balance on pretreatment variables:
with(cow, tapply(lactation, level, mean))
with(cow, tappl... |
#!/usr/bin/env Rscript
library("optparse")
library("data.table")
V="Version: 1.0"
D="Depends: R (>= 3.4.0), optparse, data.table"
a = commandArgs(trailingOnly=TRUE)
option_list = list(
make_option(c("--output_prefix"), type="character", default="annovarToMaf",
help="If provided writes resulting MAF file to... | /maftools_annovarToMaf.R | permissive | chunyangbao/cbao_utilities | R | false | false | 1,869 | r | #!/usr/bin/env Rscript
library("optparse")
library("data.table")
V="Version: 1.0"
D="Depends: R (>= 3.4.0), optparse, data.table"
a = commandArgs(trailingOnly=TRUE)
option_list = list(
make_option(c("--output_prefix"), type="character", default="annovarToMaf",
help="If provided writes resulting MAF file to... |
library(readr)
dataset <- read_csv("Downloads/dataset.csv", col_names = FALSE)
data <- dataset[, 2:14]
data_norm <- scale(data)
minPoints <- 3
epsilon <- 3
noise <- c()
for (i in 1:nrow(data_norm)) {
counter <- 0
for (j in 1:nrow(data_norm)) {
if (dist(rbind(data_norm[i, ], data_norm[j, ])) < epsilon) {
c... | /ex07/unknowndata.r | no_license | SimonGiebenhain/AnaVis | R | false | false | 874 | r | library(readr)
dataset <- read_csv("Downloads/dataset.csv", col_names = FALSE)
data <- dataset[, 2:14]
data_norm <- scale(data)
minPoints <- 3
epsilon <- 3
noise <- c()
for (i in 1:nrow(data_norm)) {
counter <- 0
for (j in 1:nrow(data_norm)) {
if (dist(rbind(data_norm[i, ], data_norm[j, ])) < epsilon) {
c... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/primary-keys.R
\name{cdm_get_pk}
\alias{cdm_get_pk}
\title{Retrieve the name of the primary key column of a \code{dm} table}
\usage{
cdm_get_pk(dm, table)
}
\arguments{
\item{dm}{A \code{dm} object.}
\item{table}{A table in the \code{dm}.}
}... | /man/cdm_get_pk.Rd | permissive | bbecane/dm | R | false | true | 861 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/primary-keys.R
\name{cdm_get_pk}
\alias{cdm_get_pk}
\title{Retrieve the name of the primary key column of a \code{dm} table}
\usage{
cdm_get_pk(dm, table)
}
\arguments{
\item{dm}{A \code{dm} object.}
\item{table}{A table in the \code{dm}.}
}... |
testlist <- list(A = structure(c(2.17107980817984e+205, 9.53818252179844e+295 ), .Dim = 1:2), B = structure(c(2.19477796793271e+294, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(5L, 7L)))
result <- do.call(multivariance:::match_rows,testlist)
str(resu... | /multivariance/inst/testfiles/match_rows/AFL_match_rows/match_rows_valgrind_files/1613122592-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 323 | r | testlist <- list(A = structure(c(2.17107980817984e+205, 9.53818252179844e+295 ), .Dim = 1:2), B = structure(c(2.19477796793271e+294, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(5L, 7L)))
result <- do.call(multivariance:::match_rows,testlist)
str(resu... |
load("mydata.rda")
data = datacsv1
# Divide orginal data into two
## Transform NA into 0 in data
for(i in c(9:14,19)){
data[, i] = ifelse(is.na(data[, i]), 0, data[, i])
}
data_index = data[c(9:14,19)]
## Score the quality of each information (row)
data_index$Score = 0
for(i in 1:7){
data_index[, 8] = data_index[... | /Project_Data_Partition.R | no_license | YurongJiang/Unsupervised-NY-property-fraud-detection-model | R | false | false | 948 | r | load("mydata.rda")
data = datacsv1
# Divide orginal data into two
## Transform NA into 0 in data
for(i in c(9:14,19)){
data[, i] = ifelse(is.na(data[, i]), 0, data[, i])
}
data_index = data[c(9:14,19)]
## Score the quality of each information (row)
data_index$Score = 0
for(i in 1:7){
data_index[, 8] = data_index[... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cv.plsRcox.R
\name{cv.plsRcox}
\alias{cv.plsRcox}
\title{Cross-validating a plsRcox-Model}
\usage{
cv.plsRcox(
data,
method = c("efron", "breslow"),
nfold = 5,
nt = 10,
plot.it = TRUE,
se = TRUE,
givefold,
scaleX = TRUE,
fol... | /man/cv.plsRcox.Rd | no_license | cran/plsRcox | R | false | true | 10,322 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cv.plsRcox.R
\name{cv.plsRcox}
\alias{cv.plsRcox}
\title{Cross-validating a plsRcox-Model}
\usage{
cv.plsRcox(
data,
method = c("efron", "breslow"),
nfold = 5,
nt = 10,
plot.it = TRUE,
se = TRUE,
givefold,
scaleX = TRUE,
fol... |
#' Determine bearish engulfing pattern using a OHLC price series
#'
#' @param x OHLC prices.
#' @return TRUE if bearish engulfing pattern detected
#' @export
bearish.engulf <- function(x) {
BT <- CandleBodyTop(x)
BB <- CandleBodyBottom(x)
Lag.BT <- quantmod::Lag(BT)
Lag.BB <- quantmod::Lag(BB)
U <- bullis... | /R/bearish.engulf.R | no_license | Roshan2540/CandleStickPattern | R | false | false | 578 | r | #' Determine bearish engulfing pattern using a OHLC price series
#'
#' @param x OHLC prices.
#' @return TRUE if bearish engulfing pattern detected
#' @export
bearish.engulf <- function(x) {
BT <- CandleBodyTop(x)
BB <- CandleBodyBottom(x)
Lag.BT <- quantmod::Lag(BT)
Lag.BB <- quantmod::Lag(BB)
U <- bullis... |
#
# This is the server logic of a Shiny web application. You can run the
# application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
##########################
# E D A #
##########################
# Def... | /Application/server.R | no_license | tomasj12/ShinyApp | R | false | false | 17,599 | r | #
# This is the server logic of a Shiny web application. You can run the
# application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
##########################
# E D A #
##########################
# Def... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GRangesUtils.R
\name{filterChrGR}
\alias{filterChrGR}
\title{Filters unwanted seqlevels from a Genomic Ranges object or similar object}
\usage{
filterChrGR(
gr = NULL,
remove = NULL,
underscore = TRUE,
standard = TRUE,
pruningMode =... | /man/filterChrGR.Rd | permissive | GreenleafLab/ArchR | R | false | true | 1,567 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GRangesUtils.R
\name{filterChrGR}
\alias{filterChrGR}
\title{Filters unwanted seqlevels from a Genomic Ranges object or similar object}
\usage{
filterChrGR(
gr = NULL,
remove = NULL,
underscore = TRUE,
standard = TRUE,
pruningMode =... |
# Exercise 4: complex Shiny UI layouts
# Load libraries so they are available
library("shiny")
# Use source() to execute the `app_ui.R` and `app_server.R` files. These will
# define the UI value and server function respectively.
source("app_ui.R")
source("app_server.R")
# You will need to fill in the `app_ui.R` file... | /exercise-4/app.R | permissive | jstnwoo-1623155/chapter-19-exercises | R | false | false | 487 | r | # Exercise 4: complex Shiny UI layouts
# Load libraries so they are available
library("shiny")
# Use source() to execute the `app_ui.R` and `app_server.R` files. These will
# define the UI value and server function respectively.
source("app_ui.R")
source("app_server.R")
# You will need to fill in the `app_ui.R` file... |
testlist <- list(A = structure(c(2.31584307392677e+77, 9.53818252170339e+295, 1.22808535475903e+146, 4.12396251261199e-221, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(5L, 7L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_row... | /multivariance/inst/testfiles/match_rows/AFL_match_rows/match_rows_valgrind_files/1613100292-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 343 | r | testlist <- list(A = structure(c(2.31584307392677e+77, 9.53818252170339e+295, 1.22808535475903e+146, 4.12396251261199e-221, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(5L, 7L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_row... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pipe.R
\name{\%>\%}
\alias{\%>\%}
\title{Pipe}
\usage{
}
\description{
Pipe a data structure forward into a function call.
}
\details{
\code{x \%>\% f()} becomes \code{f(x)}.
The pipe takes \code{x} and inserts it into the first argument of... | /man/grapes-greater-than-grapes.Rd | permissive | rhenyu/qelp | R | false | true | 1,515 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pipe.R
\name{\%>\%}
\alias{\%>\%}
\title{Pipe}
\usage{
}
\description{
Pipe a data structure forward into a function call.
}
\details{
\code{x \%>\% f()} becomes \code{f(x)}.
The pipe takes \code{x} and inserts it into the first argument of... |
## A pair of functions that cache the inverse of a matrix
## Creates a special matrix object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
## Initialize the inverse property
m <- NULL
##Set the matrix
set <- function(y) {
x <<- y
m <<- NULL... | /cachematrix_v2.R | no_license | ashwanibhagra/ProgrammingAssignment2 | R | false | false | 1,409 | r | ## A pair of functions that cache the inverse of a matrix
## Creates a special matrix object that can cache its inverse
makeCacheMatrix <- function(x = matrix()) {
## Initialize the inverse property
m <- NULL
##Set the matrix
set <- function(y) {
x <<- y
m <<- NULL... |
#-------- packages --------
library(tidyverse)
library(spdep)
library(ggthemes)
library(ggmap)
library(viridis)
library(lubridate)
library(gstat)
library(sp)
library(sf)
library(classInt)
library(lmtest)
library(tseries)
library(broom)
library(mgcv)
#-------- data and directory --------
paste0(here::here(), "/final p... | /final project/scripts/data import.R | no_license | antoniojurlina/spatial_analysis | R | false | false | 13,139 | r | #-------- packages --------
library(tidyverse)
library(spdep)
library(ggthemes)
library(ggmap)
library(viridis)
library(lubridate)
library(gstat)
library(sp)
library(sf)
library(classInt)
library(lmtest)
library(tseries)
library(broom)
library(mgcv)
#-------- data and directory --------
paste0(here::here(), "/final p... |
#:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "lupus")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "STATUS")
lrn ... | /models/openml_lupus/classification_STATUS/818e601221dccc5501618cd5d8f51482/code.R | no_license | lukaszbrzozowski/CaseStudies2019S | R | false | false | 753 | r | #:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "lupus")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "STATUS")
lrn ... |
# making calibration plots for an arbitrary outcome
# outcome_of_interest <- names(final_forests_missingness)[1]
make_calibration_plot <- function(forest, outcome_of_interest,
master=master_pool){
# -> get tau's
tau_df <- forest$tau_df
# -> add ventiles
qcut <- function(x... | /analysis_utils/calibration_plots.R | no_license | noahrsebek/match_ml_hte_mirror | R | false | false | 3,273 | r | # making calibration plots for an arbitrary outcome
# outcome_of_interest <- names(final_forests_missingness)[1]
make_calibration_plot <- function(forest, outcome_of_interest,
master=master_pool){
# -> get tau's
tau_df <- forest$tau_df
# -> add ventiles
qcut <- function(x... |
#' @include widget.r serializer.r
NULL
#' Widget_Function
#'
#' Description
Widget_Function <- R6Class(
'Widget_Function',
inherit = Widget,
public = list(
serializer = NULL,
limit = NULL,
function_name = NULL,
handle_backbone = function(msg) {
msg_limit <- msg$sy... | /kernel-r/declarativewidgets/R/widget_function.r | permissive | marami52/declarativewidgets | R | false | false | 7,062 | r | #' @include widget.r serializer.r
NULL
#' Widget_Function
#'
#' Description
Widget_Function <- R6Class(
'Widget_Function',
inherit = Widget,
public = list(
serializer = NULL,
limit = NULL,
function_name = NULL,
handle_backbone = function(msg) {
msg_limit <- msg$sy... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_amm_from_matrix.R
\name{plot_amm_from_matrix}
\alias{plot_amm_from_matrix}
\title{plot an ancestry matrix (or multiple such matrices) from its (their) matrix form}
\usage{
plot_amm_from_matrix(X)
}
\arguments{
\item{X}{input tibble with ... | /man/plot_amm_from_matrix.Rd | no_license | cran/CKMRpop | R | false | true | 1,365 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_amm_from_matrix.R
\name{plot_amm_from_matrix}
\alias{plot_amm_from_matrix}
\title{plot an ancestry matrix (or multiple such matrices) from its (their) matrix form}
\usage{
plot_amm_from_matrix(X)
}
\arguments{
\item{X}{input tibble with ... |
list.of.packages <- c("ggplot2", "showtext", "reshape2", "plyr", "stringr")
ensure.packages <- function(packages=list.of.packages) {
new.packages <- packages[!(packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)
for (package in packages) {
library(package,... | /src/plots/R/settings.R | no_license | mwibrow/baap-2018-poster | R | false | false | 3,044 | r | list.of.packages <- c("ggplot2", "showtext", "reshape2", "plyr", "stringr")
ensure.packages <- function(packages=list.of.packages) {
new.packages <- packages[!(packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)
for (package in packages) {
library(package,... |
context("Test plotting trajectory types")
test_that("test plot_trajectory_type", {
plot <- ggplot() +
theme_void()
new_plot <- plot %>%
plot_trajectory_types(trajectory_types$id, ymin = seq_along(trajectory_types$id), ymax = seq_along(trajectory_types$id) + 1, size = 1.5)
testthat::expect_true(is.ggpl... | /package/tests/testthat/test-plotting_trajectory_types.R | permissive | dynverse/dynbenchmark | R | false | false | 337 | r | context("Test plotting trajectory types")
test_that("test plot_trajectory_type", {
plot <- ggplot() +
theme_void()
new_plot <- plot %>%
plot_trajectory_types(trajectory_types$id, ymin = seq_along(trajectory_types$id), ymax = seq_along(trajectory_types$id) + 1, size = 1.5)
testthat::expect_true(is.ggpl... |
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