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 |
|---|---|---|---|---|---|---|---|---|---|
withNames =
function(x, n) {temp = data.frame(x=x,n=n);
x = temp$x;
n = temp$n;
names(x) <- n;
x} | /CTDesignExperimenter/inst/helperCode/withNames.R | no_license | professorbeautiful/CTDesignExperimenter | R | false | false | 162 | r | withNames =
function(x, n) {temp = data.frame(x=x,n=n);
x = temp$x;
n = temp$n;
names(x) <- n;
x} |
#Math E-156 Script 6B-BootstrapIntro.R
#Topic 1 - A bootstrap sampling distribution
#Start with the example from section 5.1 of the textbook
#For birth weights of NC babies, we do not know the population distribution.
NCB<-read.csv("NCBirths2004.csv"); head(NCB)
BabyWt<-NCB$Weight; hist(BabyWt, breaks = "FD")
... | /Math_E156/class6/6B-BootstrapIntro.R | no_license | ddarl4/ModernKicks | R | false | false | 5,569 | r | #Math E-156 Script 6B-BootstrapIntro.R
#Topic 1 - A bootstrap sampling distribution
#Start with the example from section 5.1 of the textbook
#For birth weights of NC babies, we do not know the population distribution.
NCB<-read.csv("NCBirths2004.csv"); head(NCB)
BabyWt<-NCB$Weight; hist(BabyWt, breaks = "FD")
... |
setwd(dir = '/Users/skick/Desktop/NYC Data Science Academy/Class_R/')
library(dplyr)
library(ggplot2)
#Question 1
#1
Champions = read.csv('Champions.csv', stringsAsFactors = FALSE)
#View(Champions)
tbl_df = filter(Champions, HomeGoal > AwayGoal)
filter(Champions, HomeTeam == 'Barcelona' | HomeTeam == 'Real Madrid')
... | /R_practice/Ggplot2_prac.R | no_license | skickham/brainteasers | R | false | false | 3,885 | r | setwd(dir = '/Users/skick/Desktop/NYC Data Science Academy/Class_R/')
library(dplyr)
library(ggplot2)
#Question 1
#1
Champions = read.csv('Champions.csv', stringsAsFactors = FALSE)
#View(Champions)
tbl_df = filter(Champions, HomeGoal > AwayGoal)
filter(Champions, HomeTeam == 'Barcelona' | HomeTeam == 'Real Madrid')
... |
get_pas_by_gene_single = function(pas_by_gene){
pas_by_gene_single = pas_by_gene[sapply(pas_by_gene, nrow) == 1]
pas_by_gene_single = pas_by_gene_single[sapply(pas_by_gene_single, function(x) x$LOCATION) != "Intron"]
length(pas_by_gene_single)
names(pas_by_gene_single) = sapply(pas_by_gene_single, function(x) x... | /R/utils.R | no_license | vallurumk/MAAPER | R | false | false | 2,479 | r | get_pas_by_gene_single = function(pas_by_gene){
pas_by_gene_single = pas_by_gene[sapply(pas_by_gene, nrow) == 1]
pas_by_gene_single = pas_by_gene_single[sapply(pas_by_gene_single, function(x) x$LOCATION) != "Intron"]
length(pas_by_gene_single)
names(pas_by_gene_single) = sapply(pas_by_gene_single, function(x) x... |
/man/obscure.sample.lt.Rd | no_license | DistanceDevelopment/WiSP | R | false | false | 3,088 | rd | ||
#====================================================================================#
# PURPOSE Test of calling the main wrapper function of the timecounts package.
# thi
#
# Authors Stefanos Kechagias, James Livsey, Vladas Pipiras, Jiajie Kong
# Date Fall 2022
# Version 4.2.1
#====... | /tests/TestFinalWrapper.R | no_license | jlivsey/countsFun | R | false | false | 8,409 | r | #====================================================================================#
# PURPOSE Test of calling the main wrapper function of the timecounts package.
# thi
#
# Authors Stefanos Kechagias, James Livsey, Vladas Pipiras, Jiajie Kong
# Date Fall 2022
# Version 4.2.1
#====... |
if(!exists("NEI")){
NEI <- readRDS("./data/summarySCC_PM25.rds")
}
if(!exists("SCC")){
SCC <- readRDS("./data/Source_Classification_Code.rds")
}
# merge the two data sets
if(!exists("NEISCC")){
NEISCC <- merge(NEI, SCC, by="SCC")
}
library(ggplot2)
# Compare emissions from moto... | /Question6.R | no_license | jschlich/Exploratory-Data-Analysis-Assignment2 | R | false | false | 1,553 | r | if(!exists("NEI")){
NEI <- readRDS("./data/summarySCC_PM25.rds")
}
if(!exists("SCC")){
SCC <- readRDS("./data/Source_Classification_Code.rds")
}
# merge the two data sets
if(!exists("NEISCC")){
NEISCC <- merge(NEI, SCC, by="SCC")
}
library(ggplot2)
# Compare emissions from moto... |
spatialAnalysis.plotStatMaps <- function(){
don <- .cdtData$EnvData$don
climMapOp <- .cdtData$EnvData$climMapOp
## titre
if(!climMapOp$title$user){
params <- .cdtData$EnvData$statpars$params
titre1 <- stringr::str_to_title(params$time.series$out.series)
titre2 <- tclvalue(.cdtD... | /R/cdtSpatialAnalysis_Display.R | no_license | YabOusmane/CDT | R | false | false | 19,647 | r |
spatialAnalysis.plotStatMaps <- function(){
don <- .cdtData$EnvData$don
climMapOp <- .cdtData$EnvData$climMapOp
## titre
if(!climMapOp$title$user){
params <- .cdtData$EnvData$statpars$params
titre1 <- stringr::str_to_title(params$time.series$out.series)
titre2 <- tclvalue(.cdtD... |
# read and load data
library(glmnet)
csv_JPN_all <- 'Z:/Uni Nils/Energy Science Master/Masterarbeit/Python/Marc GranovetterModell/pygranovetter/Workprogress Scripts/Auswertung/Arrays_all_cluster_simulations/Relaxed Lasso Data/JPN_all_Datframe_100000Simulations.csv'
csv_JPN_only_tipped <- 'Z:/Uni Nils/Energy Science ... | /Relaxed Lasso Regressions/RProject_JPN/RelaxedLasso_FinalAnalysis_JPN.R | no_license | NilsDunker/Master-thesis-Dunker | R | false | false | 15,086 | r | # read and load data
library(glmnet)
csv_JPN_all <- 'Z:/Uni Nils/Energy Science Master/Masterarbeit/Python/Marc GranovetterModell/pygranovetter/Workprogress Scripts/Auswertung/Arrays_all_cluster_simulations/Relaxed Lasso Data/JPN_all_Datframe_100000Simulations.csv'
csv_JPN_only_tipped <- 'Z:/Uni Nils/Energy Science ... |
\name{macc-package}
\alias{macc-package}
\docType{package}
\title{
Causal Mediation Analysis under Correlated Errors
}
\description{
macc performs causal mediation analysis under confounding or correlated errors. This package includes a single level mediation model, a two-level mediation model and a three-level mediati... | /man/macc-package.Rd | no_license | cran/macc | R | false | false | 996 | rd | \name{macc-package}
\alias{macc-package}
\docType{package}
\title{
Causal Mediation Analysis under Correlated Errors
}
\description{
macc performs causal mediation analysis under confounding or correlated errors. This package includes a single level mediation model, a two-level mediation model and a three-level mediati... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/steps-blogdown.R
\name{step_build_blogdown}
\alias{step_build_blogdown}
\title{Step: Build a Blogdown Site}
\usage{
step_build_blogdown(...)
}
\arguments{
\item{...}{
Arguments passed on to \code{\link[blogdown:build_site]{blogdown::build_s... | /man/step_build_blogdown.Rd | no_license | ropensci/tic | R | false | true | 1,698 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/steps-blogdown.R
\name{step_build_blogdown}
\alias{step_build_blogdown}
\title{Step: Build a Blogdown Site}
\usage{
step_build_blogdown(...)
}
\arguments{
\item{...}{
Arguments passed on to \code{\link[blogdown:build_site]{blogdown::build_s... |
library(ape)
testtree <- read.tree("262_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="262_0_unrooted.txt") | /codeml_files/newick_trees_processed/262_0/rinput.R | no_license | DaniBoo/cyanobacteria_project | R | false | false | 133 | r | library(ape)
testtree <- read.tree("262_0.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="262_0_unrooted.txt") |
#:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "chscase_census5")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "binaryClass")
lrn = m... | /models/openml_chscase_census5/classification_binaryClass/021fb729ee89ca332f9feacc25c36c14/code.R | no_license | pysiakk/CaseStudies2019S | R | false | false | 692 | r | #:# libraries
library(digest)
library(mlr)
library(OpenML)
library(farff)
#:# config
set.seed(1)
#:# data
dataset <- getOMLDataSet(data.name = "chscase_census5")
head(dataset$data)
#:# preprocessing
head(dataset$data)
#:# model
task = makeClassifTask(id = "task", data = dataset$data, target = "binaryClass")
lrn = m... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/as.node.R
\name{as.node}
\alias{as.node}
\alias{as.node.character}
\alias{as.node.tree}
\title{Conversion to a node}
\usage{
as.node(x, ...)
\method{as.node}{character}(x, ...)
\method{as.node}{tree}(x, ...)
}
\arguments{
\item{x}{An object... | /man/as.node.Rd | no_license | paulponcet/oak | R | false | true | 856 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/as.node.R
\name{as.node}
\alias{as.node}
\alias{as.node.character}
\alias{as.node.tree}
\title{Conversion to a node}
\usage{
as.node(x, ...)
\method{as.node}{character}(x, ...)
\method{as.node}{tree}(x, ...)
}
\arguments{
\item{x}{An object... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/forest_plot_1-to-many.R
\name{format_1_to_many}
\alias{format_1_to_many}
\title{Format MR results for a 1-to-many forest plot}
\usage{
format_1_to_many(
mr_res,
b = "b",
se = "se",
exponentiate = FALSE,
ao_slc = FALSE,
by = NULL,
... | /man/format_1_to_many.Rd | permissive | MRCIEU/TwoSampleMR | R | false | true | 1,819 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/forest_plot_1-to-many.R
\name{format_1_to_many}
\alias{format_1_to_many}
\title{Format MR results for a 1-to-many forest plot}
\usage{
format_1_to_many(
mr_res,
b = "b",
se = "se",
exponentiate = FALSE,
ao_slc = FALSE,
by = NULL,
... |
## makeCacheMatrix is a function that generates a matrix
## and caches its inverse using the solve function in R.
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
set <- function(y) {
x <<- y
m <<- NULL
}
get <- function() x
setinv <- function(solve) m <<- solve
getinv <- function() m
list(... | /cachematrix.R | no_license | ec953/ProgrammingAssignment2 | R | false | false | 909 | r | ## makeCacheMatrix is a function that generates a matrix
## and caches its inverse using the solve function in R.
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
set <- function(y) {
x <<- y
m <<- NULL
}
get <- function() x
setinv <- function(solve) m <<- solve
getinv <- function() m
list(... |
##' MScPack
##' Description: Random generation of DFM with s = 2 and h = 3
##' Author: Rafael Barcellos
##' Last updated 21st June 2014
##' R 3.1.0
# defining parms ----------------------------------------------------------
TT <- 500 # time span
psi <- c(0.02, 0.19, 0.36, 0.02, 0.02,
0.19, 0.19, 0.36, 0.36,... | /tests/RandGenDfm2Var3.R | no_license | rbarcellos/MScPack | R | false | false | 1,937 | r | ##' MScPack
##' Description: Random generation of DFM with s = 2 and h = 3
##' Author: Rafael Barcellos
##' Last updated 21st June 2014
##' R 3.1.0
# defining parms ----------------------------------------------------------
TT <- 500 # time span
psi <- c(0.02, 0.19, 0.36, 0.02, 0.02,
0.19, 0.19, 0.36, 0.36,... |
library(tidyverse)
melbourne <- read.csv("melb_data_raw.csv", header=TRUE)
glimpse(melbourne)
# We don't need method, seller, or address.
melbourne <- subset(melbourne, select = -c(Address, SellerG, Method))
# telling R which predictors are categorical
melbourne$Type <- factor(melbourne$Type)
melbourne$Regionname <-... | /melbourne-analysis.R | no_license | mds9b/melbourne-housing | R | false | false | 2,125 | r | library(tidyverse)
melbourne <- read.csv("melb_data_raw.csv", header=TRUE)
glimpse(melbourne)
# We don't need method, seller, or address.
melbourne <- subset(melbourne, select = -c(Address, SellerG, Method))
# telling R which predictors are categorical
melbourne$Type <- factor(melbourne$Type)
melbourne$Regionname <-... |
library(EMCluster)
b = function(init_p,init_u1,init_u2,init_s1,init_s2,TOL){
n = 200;
x = rnorm(n,0,1);
y = rnorm(n,0,5);
u = runif(n,0,1);
mix = 1:n;
for(i in 1:n){
if(u[i]<0.4){
mix[i] = x[i];
}else{
mix[i] = y[i];
}
}
p_old = 0.1;
u1_old = 0.3;
s1_old = 2.1;
u2_old = 0.1... | /r.bandaMA471lab3/b.r | no_license | Santhoshrbanda/safd | R | false | false | 1,672 | r | library(EMCluster)
b = function(init_p,init_u1,init_u2,init_s1,init_s2,TOL){
n = 200;
x = rnorm(n,0,1);
y = rnorm(n,0,5);
u = runif(n,0,1);
mix = 1:n;
for(i in 1:n){
if(u[i]<0.4){
mix[i] = x[i];
}else{
mix[i] = y[i];
}
}
p_old = 0.1;
u1_old = 0.3;
s1_old = 2.1;
u2_old = 0.1... |
#ui.R for pot randomisation based on randomised block desing
#Load shiny package
library(shiny)
# Define UI for dataset viewer application
shinyUI(navbarPage("RandomisationApps",
#Tab with explanation
tabPanel("About",
"These apps are developed to ease the randomized design of an experiment. Currentl... | /ui.R | no_license | IkoKoevoets/RandomizationApp | R | false | false | 2,517 | r | #ui.R for pot randomisation based on randomised block desing
#Load shiny package
library(shiny)
# Define UI for dataset viewer application
shinyUI(navbarPage("RandomisationApps",
#Tab with explanation
tabPanel("About",
"These apps are developed to ease the randomized design of an experiment. Currentl... |
RDA2
A
2
196866
131840
1026
1
262153
5
value
787
134
787
41
16
1
262153
11
effect_test
10
1
0
10
1
1
14
1
3
14
1
0.2
14
1
0.5
14
1
1
10
1
0
10
1
0
10
1
0
16
1
262153
10
simstats0c
10
1
NA
14
1
0
16
1
262153
0
10
1
0
14
1
1
10
1
1
10
1
0
14
1
0.2
14
1
1
14
1
0
14
1
12345
14
1
0.05
14
1
0.05
14
1
0.2
14
1
0.3
14
1
0.3
1... | /R/lib/RSienaTest/unitTests/behaviorObjective.Rd | no_license | BRICOMATA/Bricomata_ | R | false | false | 24,382 | rd | RDA2
A
2
196866
131840
1026
1
262153
5
value
787
134
787
41
16
1
262153
11
effect_test
10
1
0
10
1
1
14
1
3
14
1
0.2
14
1
0.5
14
1
1
10
1
0
10
1
0
10
1
0
16
1
262153
10
simstats0c
10
1
NA
14
1
0
16
1
262153
0
10
1
0
14
1
1
10
1
1
10
1
0
14
1
0.2
14
1
1
14
1
0
14
1
12345
14
1
0.05
14
1
0.05
14
1
0.2
14
1
0.3
14
1
0.3
1... |
#【讀入資料】
install.packages("xlsx")
library(xlsx)
brain <-read.xlsx(file ="data/brain.xlsx",sheetIndex = 1)
babies =read.csv(file="data/babies.txt",sep = " ")
cancer <- read.csv("data/cancer.csv", header=T, sep = ",")
#【相關常態判別】
#【plot】
plot(~perimeter_worst+area_worst,data = cancer)
plot(~perimeter_worst+area_worst+smo... | /data_cleaning.R | no_license | lucy851023/BigDataTeam_exercise | R | false | false | 2,999 | r | #【讀入資料】
install.packages("xlsx")
library(xlsx)
brain <-read.xlsx(file ="data/brain.xlsx",sheetIndex = 1)
babies =read.csv(file="data/babies.txt",sep = " ")
cancer <- read.csv("data/cancer.csv", header=T, sep = ",")
#【相關常態判別】
#【plot】
plot(~perimeter_worst+area_worst,data = cancer)
plot(~perimeter_worst+area_worst+smo... |
library(magick)
library(cowplot)
cfr1_plot <- image_read("~/Desktop/Covid disparities/health disparity/Output/CFR Total Univariable.png")
cfr2_plot <- image_read("~/Desktop/Covid disparities/health disparity/Output/CFR Total Multivariable.png")
cfr2_crop <- image_crop(cfr2_plot, "725x1200+550")
img <- c(cfr1_p... | /Scripts/FigureGen_FigureS5.R | no_license | lin-lab/COVID-Health-Disparities | R | false | false | 539 | r | library(magick)
library(cowplot)
cfr1_plot <- image_read("~/Desktop/Covid disparities/health disparity/Output/CFR Total Univariable.png")
cfr2_plot <- image_read("~/Desktop/Covid disparities/health disparity/Output/CFR Total Multivariable.png")
cfr2_crop <- image_crop(cfr2_plot, "725x1200+550")
img <- c(cfr1_p... |
## ----global_options, include = FALSE------------------------------------------------
try(source("../../.Rprofile"))
## -----------------------------------------------------------------------------------
# polynomial coefficients
set.seed(123)
ar_coef_poly <- rnorm(4)
# time right hand side matrix
ar_t <- 0:3
ar_pow... | /linreg/polynomial/htmlpdfr/fs_poly_fit.R | permissive | FanWangEcon/R4Econ | R | false | false | 2,192 | r | ## ----global_options, include = FALSE------------------------------------------------
try(source("../../.Rprofile"))
## -----------------------------------------------------------------------------------
# polynomial coefficients
set.seed(123)
ar_coef_poly <- rnorm(4)
# time right hand side matrix
ar_t <- 0:3
ar_pow... |
require(pathview)
require(KEGGREST)
publicPathlines = readLines("data/publicPath.txt")
sim.mol.data2=function(mol.type=c("gene","gene.ko","cpd")[1], id.type=NULL, species="hsa", discrete=FALSE, nmol=1000, nexp=1, rand.seed=100)
{
msg.fmt="\"%s\" is not a good \"%s\" \"%s\" ID type for simulation!"
msg.fmt2="\"%... | /public/scripts/sim.mol.data2.R | no_license | gauravp99/pathviewdev | R | false | false | 3,305 | r | require(pathview)
require(KEGGREST)
publicPathlines = readLines("data/publicPath.txt")
sim.mol.data2=function(mol.type=c("gene","gene.ko","cpd")[1], id.type=NULL, species="hsa", discrete=FALSE, nmol=1000, nexp=1, rand.seed=100)
{
msg.fmt="\"%s\" is not a good \"%s\" \"%s\" ID type for simulation!"
msg.fmt2="\"%... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ftrl.Dataset.R
\name{dim.ftrl.Dataset}
\alias{dim.ftrl.Dataset}
\title{Dimensions of ftrl.Dataset}
\usage{
\method{dim}{ftrl.Dataset}(x)
}
\arguments{
\item{x}{Object of class \code{ftrl.Dataset}}
}
\description{
Returns a vector of numbers o... | /man/dim.ftrl.Dataset.Rd | no_license | yanyachen/rFTRLProximal | R | false | true | 517 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ftrl.Dataset.R
\name{dim.ftrl.Dataset}
\alias{dim.ftrl.Dataset}
\title{Dimensions of ftrl.Dataset}
\usage{
\method{dim}{ftrl.Dataset}(x)
}
\arguments{
\item{x}{Object of class \code{ftrl.Dataset}}
}
\description{
Returns a vector of numbers o... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/st_sample_geotools.R
\name{st_sample_geotools}
\alias{st_sample_geotools}
\title{st_sample_geotools}
\usage{
st_sample_geotools(
geodata,
n,
fraction = NULL,
weight_var,
type = "random",
iter = 9,
...
)
}
\arguments{
\item{geoda... | /man/st_sample_geotools.Rd | no_license | BAAQMD/geotools | R | false | true | 1,414 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/st_sample_geotools.R
\name{st_sample_geotools}
\alias{st_sample_geotools}
\title{st_sample_geotools}
\usage{
st_sample_geotools(
geodata,
n,
fraction = NULL,
weight_var,
type = "random",
iter = 9,
...
)
}
\arguments{
\item{geoda... |
\name{dagR-package}
\Rdversion{1.1}
\alias{dagR-package}
\alias{dagR}
\docType{package}
\title{
R functions for directed acyclic graphs
}
\description{
The package dagR (pronounce "dagger") contains a couple of functions to draw, manipulate and evaluate directed acyclic graphs (DAG), with a focus on epidemiologic appli... | /man/dagR-package.Rd | no_license | mjaquiery/dagR | R | false | false | 2,946 | rd | \name{dagR-package}
\Rdversion{1.1}
\alias{dagR-package}
\alias{dagR}
\docType{package}
\title{
R functions for directed acyclic graphs
}
\description{
The package dagR (pronounce "dagger") contains a couple of functions to draw, manipulate and evaluate directed acyclic graphs (DAG), with a focus on epidemiologic appli... |
####**********************************************************************
####**********************************************************************
####
#### RANDOM SURVIVAL FOREST 3.6.4
####
#### Copyright 2013, Cleveland Clinic Foundation
####
#### This program is free software; you can redistribute it and/or
##... | /R/max.subtree.R | no_license | cran/randomSurvivalForest | R | false | false | 15,018 | r | ####**********************************************************************
####**********************************************************************
####
#### RANDOM SURVIVAL FOREST 3.6.4
####
#### Copyright 2013, Cleveland Clinic Foundation
####
#### This program is free software; you can redistribute it and/or
##... |
# <<- operator can be used to assign a value to an object in an environment
# that is different from the current environment
## The first function, makeVector creates a special "vector"
## which is really a list containing a function to
## set the value of the vector
## get the value of the vector
## set the value of... | /Cache Vector Mean.R | no_license | difu1994/Week-3 | R | false | false | 2,107 | r | # <<- operator can be used to assign a value to an object in an environment
# that is different from the current environment
## The first function, makeVector creates a special "vector"
## which is really a list containing a function to
## set the value of the vector
## get the value of the vector
## set the value of... |
function(input, output) {
library(dplyr)
temperatures_by_state <- read.csv("Data/temperature.txt", header = TRUE, stringsAsFactors = FALSE)
temperatures_by_state <- temperatures_by_state[order(-temperatures_by_state$Avg..F),]
# create a vector of 50 in descending order
a1 <- seq(1:50)
a1 <- as.data.frame(a1)
a1 <- a... | /State_Scores/helpers.R | permissive | bthomas-ds/developing-data-products | R | false | false | 1,704 | r | function(input, output) {
library(dplyr)
temperatures_by_state <- read.csv("Data/temperature.txt", header = TRUE, stringsAsFactors = FALSE)
temperatures_by_state <- temperatures_by_state[order(-temperatures_by_state$Avg..F),]
# create a vector of 50 in descending order
a1 <- seq(1:50)
a1 <- as.data.frame(a1)
a1 <- a... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/query_pfts.R
\name{query_pfts}
\alias{query_pfts}
\title{Retrieve PFT ID, name, and type from BETY}
\usage{
query_pfts(dbcon, pft_names, modeltype = NULL, strict = FALSE)
}
\arguments{
\item{dbcon}{Database connection object}
\item{pft_names... | /base/db/man/query_pfts.Rd | permissive | ashiklom/pecan | R | false | true | 667 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/query_pfts.R
\name{query_pfts}
\alias{query_pfts}
\title{Retrieve PFT ID, name, and type from BETY}
\usage{
query_pfts(dbcon, pft_names, modeltype = NULL, strict = FALSE)
}
\arguments{
\item{dbcon}{Database connection object}
\item{pft_names... |
setwd("//ahmct-065/teams/PMRF/Amir")
library(data.table)
library(lubridate)
library(anytime)
library(purrr)
LEMO_WorkOrder.df=fread(file="./bin/Final Datasets/LEMO_WorkOrder+odom.csv", sep=",", header=TRUE)
LEMO_WorkOrder.df=cbind(LEMO_WorkOrder.df, ID=seq.int(nrow(LEMO_WorkOrder.df)))
tempLEMO.df=LEMO_WorkOrder.df[,... | /MATCH(SWITRS, WorkOrderNo_Activity_Workdate).R | no_license | AmirAli-N/PMRF-DataAnalysis | R | false | false | 2,984 | r | setwd("//ahmct-065/teams/PMRF/Amir")
library(data.table)
library(lubridate)
library(anytime)
library(purrr)
LEMO_WorkOrder.df=fread(file="./bin/Final Datasets/LEMO_WorkOrder+odom.csv", sep=",", header=TRUE)
LEMO_WorkOrder.df=cbind(LEMO_WorkOrder.df, ID=seq.int(nrow(LEMO_WorkOrder.df)))
tempLEMO.df=LEMO_WorkOrder.df[,... |
#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
# Define UI for application that draws a histogram
ui <- fluidPage(
# Application title
t... | /app.R | no_license | andreferraribr/sankey | R | false | false | 1,424 | r | #
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
# Define UI for application that draws a histogram
ui <- fluidPage(
# Application title
t... |
ggplot(blah3, aes(x=Month, y=Principal, group=group, col=group, fill=group)) +
+ geom_point() +
+ geom_smooth(size=1)
blah$group <- "15 year"
blah2$group <- "30 year"
blah3 <- rbind(blah,blah2)
| /graphing notes.R | no_license | Noah-Hughes/DataProducts | R | false | false | 207 | r | ggplot(blah3, aes(x=Month, y=Principal, group=group, col=group, fill=group)) +
+ geom_point() +
+ geom_smooth(size=1)
blah$group <- "15 year"
blah2$group <- "30 year"
blah3 <- rbind(blah,blah2)
|
rm(list=ls())
library(shiny); library(Reol); library(xml2); library(rnbn); library(stringr)
# Quick fix for Reol bug when matching EOL entries for instances where search
# returns more than one result for the same EOL ID
insertSource("./NBN_hack_series/BirdBingo/MatchTaxatoEOLID.R", package = "Reol", functions = "Ma... | /BirdBingo/shiny_app/ui.R | no_license | christophercooney/NBN_hack_series | R | false | false | 7,539 | r |
rm(list=ls())
library(shiny); library(Reol); library(xml2); library(rnbn); library(stringr)
# Quick fix for Reol bug when matching EOL entries for instances where search
# returns more than one result for the same EOL ID
insertSource("./NBN_hack_series/BirdBingo/MatchTaxatoEOLID.R", package = "Reol", functions = "Ma... |
# Reading data set
data<-read.table("household_power_consumption.txt",sep=";",header=T)
data$Date
tomatch <- c(grep("\\b1/2/2007\\b", data$Date),grep("\\b2/2/2007\\b", data$Date))
df <- data[tomatch,]
# Convert to date and time
df$Date <- as.Date(df$Date, "%d/%m/%Y")
df$Time <- strptime(df$Time, "%H:%M:%S")
d... | /Plot2.R | no_license | jvrojas/ExData_Plotting1 | R | false | false | 685 | r | # Reading data set
data<-read.table("household_power_consumption.txt",sep=";",header=T)
data$Date
tomatch <- c(grep("\\b1/2/2007\\b", data$Date),grep("\\b2/2/2007\\b", data$Date))
df <- data[tomatch,]
# Convert to date and time
df$Date <- as.Date(df$Date, "%d/%m/%Y")
df$Time <- strptime(df$Time, "%H:%M:%S")
d... |
library(dplyr)
library(readr)
library(metafor)
###glmm_fe
ptm<-proc.time()
bias=c()
bias.prop=c()
RMSE=c()
RMSE.prop=c()
coverage=c()
##dobby1
dobby1<-function(vec)as.numeric(as.character(vec))
for(i in 1:792){
data.path<-paste0("sim_data/scenario_", i, ".csv")
dat<-suppressWarnings(read_csv(data.path))
##u... | /sim13/analysis_glmm_fe.R | no_license | ShawnFries/meta_code | R | false | false | 1,911 | r | library(dplyr)
library(readr)
library(metafor)
###glmm_fe
ptm<-proc.time()
bias=c()
bias.prop=c()
RMSE=c()
RMSE.prop=c()
coverage=c()
##dobby1
dobby1<-function(vec)as.numeric(as.character(vec))
for(i in 1:792){
data.path<-paste0("sim_data/scenario_", i, ".csv")
dat<-suppressWarnings(read_csv(data.path))
##u... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{ppiIDN2012}
\alias{ppiIDN2012}
\title{Poverty Probability Index (PPI) lookup table for Indonesia using legacy
poverty definitions}
\format{
A data frame with 4 columns and 101 rows:
\describe{
\item{\code{score}}{P... | /man/ppiIDN2012.Rd | permissive | katilingban/ppitables | R | false | true | 1,376 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{ppiIDN2012}
\alias{ppiIDN2012}
\title{Poverty Probability Index (PPI) lookup table for Indonesia using legacy
poverty definitions}
\format{
A data frame with 4 columns and 101 rows:
\describe{
\item{\code{score}}{P... |
library(ISLR)
glm.model = glm(default~income+balance,data=Default,family=binomial)
glm.model
set.seed(1)
train = sample(nrow(Default),8000)
glm.model = glm(default~income+balance, data=Default, family=binomial, subset=train)
glm.prob = predict(glm.model,newdata=Default[-train,], type="response")
glm.pred = rep("No... | /Chapter 5 Resampling methods/Q5/q5.r | no_license | bhrzali/ISLR_assignments_applied | R | false | false | 1,219 | r |
library(ISLR)
glm.model = glm(default~income+balance,data=Default,family=binomial)
glm.model
set.seed(1)
train = sample(nrow(Default),8000)
glm.model = glm(default~income+balance, data=Default, family=binomial, subset=train)
glm.prob = predict(glm.model,newdata=Default[-train,], type="response")
glm.pred = rep("No... |
ranking <- function(tournament){ # tournament odpowiada macierzy A z artyułu
n <- dim(tournament)[1]
matches_matrix <- tournament + t(tournament) # macierz M
matches_sums <- rowSums(matches_matrix) # wektor m
scores <- rowSums(tournament, na.rm = TRUE)/matches_sums #wektor s
matches_centered <- matches_... | /simulations.R | no_license | jacek789/ranking | R | false | false | 4,523 | r | ranking <- function(tournament){ # tournament odpowiada macierzy A z artyułu
n <- dim(tournament)[1]
matches_matrix <- tournament + t(tournament) # macierz M
matches_sums <- rowSums(matches_matrix) # wektor m
scores <- rowSums(tournament, na.rm = TRUE)/matches_sums #wektor s
matches_centered <- matches_... |
/第11章 地理空间型图表/深圳地铁线路案例/深圳地铁线路图.R | no_license | EasyChart/Beautiful-Visualization-with-R | R | false | false | 3,674 | r | ||
#' Density computation on x axis.
#'
#' Horizontal version of \code{\link[ggplot2]{stat_ydensity}}().
#' @inheritParams ggplot2::stat_ydensity
#' @export
stat_xdensity <- function(mapping = NULL, data = NULL,
geom = "violinh", position = "dodgev",
...,
... | /R/stat-xdensity.R | no_license | mjskay/ggstance | R | false | false | 2,971 | r | #' Density computation on x axis.
#'
#' Horizontal version of \code{\link[ggplot2]{stat_ydensity}}().
#' @inheritParams ggplot2::stat_ydensity
#' @export
stat_xdensity <- function(mapping = NULL, data = NULL,
geom = "violinh", position = "dodgev",
...,
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ThreadNet_Misc.R
\name{make_subsets}
\alias{make_subsets}
\title{make_subsets}
\usage{
make_subsets(d, n)
}
\arguments{
\item{d}{data frame with occurrences or events}
\item{n}{number of buckets}
}
\value{
list of smaller data frames
}
\desc... | /man/make_subsets.Rd | no_license | ThreadNet/ThreadNet | R | false | true | 399 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ThreadNet_Misc.R
\name{make_subsets}
\alias{make_subsets}
\title{make_subsets}
\usage{
make_subsets(d, n)
}
\arguments{
\item{d}{data frame with occurrences or events}
\item{n}{number of buckets}
}
\value{
list of smaller data frames
}
\desc... |
skisloplot <- function (RSinput= 30, ytop = 100) {
plot(RSvector, nnt, xaxs="i", yaxs="i", ## log='y',
xlim=c(0, 50),
ylim=c(0, ytop), type="l", lwd=5,
main = "Number Needed to Treat by Recurrence Score",
xlab="Recurrence score", ylab="Number needed to treat")
AERiskTable = c(... | /inst/shinyAE/skislope.R | no_license | lilyokc/NNTbiomarkerHome | R | false | false | 1,629 | r | skisloplot <- function (RSinput= 30, ytop = 100) {
plot(RSvector, nnt, xaxs="i", yaxs="i", ## log='y',
xlim=c(0, 50),
ylim=c(0, ytop), type="l", lwd=5,
main = "Number Needed to Treat by Recurrence Score",
xlab="Recurrence score", ylab="Number needed to treat")
AERiskTable = c(... |
/etc/howm-doc/README.ja.rd | no_license | rsvdpbr/emacs-config | R | false | false | 65,506 | rd | ||
library(DEXSeq)
library(multicore)
source('~/Documents/Rscripts/120704-sortDataFrame.R')
setwd('~/Documents/RNAdata/danBatch1/dexSeq_count/')
samples = c('long1', 'long2', 'long3', 'short1', 'short2', 'short3')
# Read in design matrix
dm = read.csv('../bowtieGem/revHTSeq/designMatrix.csv')
dm = dm[,c(1,2,4,5)]
conditi... | /PhD/rnaSeqBatch1/131105_DEXSeq.R | no_license | dvbrown/Rscripts | R | false | false | 3,613 | r | library(DEXSeq)
library(multicore)
source('~/Documents/Rscripts/120704-sortDataFrame.R')
setwd('~/Documents/RNAdata/danBatch1/dexSeq_count/')
samples = c('long1', 'long2', 'long3', 'short1', 'short2', 'short3')
# Read in design matrix
dm = read.csv('../bowtieGem/revHTSeq/designMatrix.csv')
dm = dm[,c(1,2,4,5)]
conditi... |
#Author: Supat Thongjuea, MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, UK
#Contact email : supat.thongjuea@ndcls.ox.ac.uk or supat.thongjuea@gmail.com
#Maintainer: Supat Thongjuea and Alice Giustacchini
#Title: Single-cell Transcriptomics Uncovers Distinct and Clini... | /Fig3a_and_3b/Script-to-generate-data-for-GSEA-analysis.R | no_license | supatt-lab/Giustacchini-Thongjuea-et-al.-Nat.Med.2017 | R | false | false | 2,897 | r | #Author: Supat Thongjuea, MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, UK
#Contact email : supat.thongjuea@ndcls.ox.ac.uk or supat.thongjuea@gmail.com
#Maintainer: Supat Thongjuea and Alice Giustacchini
#Title: Single-cell Transcriptomics Uncovers Distinct and Clini... |
png(filename='plot2.png',bg='transparent')
data<-read.table('household_power_consumption.txt',header=TRUE,sep=';',nrows=71000,colClasses='character')
power<-subset(data,data$Date=='1/2/2007'|data$Date=='2/2/2007')
power$DateTime <- as.POSIXct(paste(power$Date, power$Time), format="%d/%m/%Y %H:%M:%S")
ap<-power$'Global... | /plot2.R | no_license | MisterNi/ExData_Plotting1 | R | false | false | 462 | r | png(filename='plot2.png',bg='transparent')
data<-read.table('household_power_consumption.txt',header=TRUE,sep=';',nrows=71000,colClasses='character')
power<-subset(data,data$Date=='1/2/2007'|data$Date=='2/2/2007')
power$DateTime <- as.POSIXct(paste(power$Date, power$Time), format="%d/%m/%Y %H:%M:%S")
ap<-power$'Global... |
library(caret); library(kernlab); data("spam") # Importação do pacote "caret" e do dateset "spam"
folds <- createFolds(y=spam$type, k = 10, list = TRUE, returnTrain = TRUE) # Criação dos k-folds, 10 k-folds
sapply(folds, length)
| /cross-validation.r | no_license | diegofsousa/ExampleOfK-fold | R | false | false | 233 | r | library(caret); library(kernlab); data("spam") # Importação do pacote "caret" e do dateset "spam"
folds <- createFolds(y=spam$type, k = 10, list = TRUE, returnTrain = TRUE) # Criação dos k-folds, 10 k-folds
sapply(folds, length)
|
#' @param opt.criterion Optimality criterion that bandwidth is designed to
#' optimize. The options are:
#'
#' \describe{
#'
#' \item{\code{"MSE"}}{Finite-sample maximum MSE}
#'
#' \item{\code{"FLCI"}}{Length of (fixed-length) two-sided
#' confidence intervals.}
#'
#' \item{\code{"OCI"}}{Given qu... | /man-roxygen/RDoptBW.R | no_license | mdroste/RDHonest | R | false | false | 958 | r | #' @param opt.criterion Optimality criterion that bandwidth is designed to
#' optimize. The options are:
#'
#' \describe{
#'
#' \item{\code{"MSE"}}{Finite-sample maximum MSE}
#'
#' \item{\code{"FLCI"}}{Length of (fixed-length) two-sided
#' confidence intervals.}
#'
#' \item{\code{"OCI"}}{Given qu... |
#' Get population data
#'
#' @param country Country name
#' @param iso3c ISO 3C Country Code
#' @param simple_SEIR Logical. Is the population for the \code{simple_SEIR}.
#' Default = FALSE
#'
#' @return Population data.frame
#' @importFrom utils head tail
#' @export
get_population <- function(country = NULL, iso3c =... | /R/population.R | permissive | tdm32/squire | R | false | false | 2,830 | r | #' Get population data
#'
#' @param country Country name
#' @param iso3c ISO 3C Country Code
#' @param simple_SEIR Logical. Is the population for the \code{simple_SEIR}.
#' Default = FALSE
#'
#' @return Population data.frame
#' @importFrom utils head tail
#' @export
get_population <- function(country = NULL, iso3c =... |
## last modified June 2002
grpintprob <- function(mixdat, mixpar, dist, constr)
{
m <- nrow(mixdat)
k <- nrow(mixpar)
mu <- mixpar[, 2]
sigma <- mixpar[, 3]
if (dist == "norm") {
par1 <- mu
par2 <- sigma
mixcdf <- t(sapply(mixdat[-m, 1], pnorm, par1, par2))
... | /R/grpintprob.R | no_license | cran/mixdist | R | false | false | 1,471 | r | ## last modified June 2002
grpintprob <- function(mixdat, mixpar, dist, constr)
{
m <- nrow(mixdat)
k <- nrow(mixpar)
mu <- mixpar[, 2]
sigma <- mixpar[, 3]
if (dist == "norm") {
par1 <- mu
par2 <- sigma
mixcdf <- t(sapply(mixdat[-m, 1], pnorm, par1, par2))
... |
library(vlad)
### Name: racusum_arl_sim
### Title: Compute ARLs of RA-CUSUM control charts using simulation
### Aliases: racusum_arl_sim
### ** Examples
## Not run:
##D library("vlad")
##D library("spcadjust")
##D set.seed(1234)
##D data("cardiacsurgery")
##D df1 <- subset(cardiacsurgery, select=c(Parsonnet, statu... | /data/genthat_extracted_code/vlad/examples/racusum_arl_sim.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 2,040 | r | library(vlad)
### Name: racusum_arl_sim
### Title: Compute ARLs of RA-CUSUM control charts using simulation
### Aliases: racusum_arl_sim
### ** Examples
## Not run:
##D library("vlad")
##D library("spcadjust")
##D set.seed(1234)
##D data("cardiacsurgery")
##D df1 <- subset(cardiacsurgery, select=c(Parsonnet, statu... |
# This script tests the change_speed() function
input_signal <- read.csv("data/bark.csv", colClasses=c('numeric'))[[1]]
test_that("Result of changing the speed of a known input signal with a rate of 2 matches the expected output", {
expected_output <- read.table("data/change_speed/bark_double_speed.csv", colClasses... | /tests/testthat/test_change_speed.R | permissive | UBC-MDS/AudioFilters_R | R | false | false | 1,276 | r | # This script tests the change_speed() function
input_signal <- read.csv("data/bark.csv", colClasses=c('numeric'))[[1]]
test_that("Result of changing the speed of a known input signal with a rate of 2 matches the expected output", {
expected_output <- read.table("data/change_speed/bark_double_speed.csv", colClasses... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/r_squared_poisson.R
\name{r_squared_poisson}
\alias{r_squared_poisson}
\title{Pseudo R-Squared regarding Poisson deviance}
\usage{
r_squared_poisson(actual, predicted, w = NULL, ...)
}
\arguments{
\item{actual}{Observed values.}
\item{predic... | /release/MetricsWeighted/man/r_squared_poisson.Rd | no_license | JosepER/MetricsWeighted | R | false | true | 759 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/r_squared_poisson.R
\name{r_squared_poisson}
\alias{r_squared_poisson}
\title{Pseudo R-Squared regarding Poisson deviance}
\usage{
r_squared_poisson(actual, predicted, w = NULL, ...)
}
\arguments{
\item{actual}{Observed values.}
\item{predic... |
#SplitPlaysByWeek
setwd('F:/BigDataBowl2021')
games = read.csv('games.csv')
load('FinalPlays.Rdata')
# load('Combined2018PassingData.RData')
# w1Plays = plays[plays$gameId %in% games[games$week == 1,'gameId'],]
# w2Plays = plays[plays$gameId %in% games[games$week == 2,'gameId'],]
# w3Plays = plays[plays$ga... | /SplitPlaysByWeek.R | no_license | prestonbiro/BigDataBowl2020 | R | false | false | 1,715 | r | #SplitPlaysByWeek
setwd('F:/BigDataBowl2021')
games = read.csv('games.csv')
load('FinalPlays.Rdata')
# load('Combined2018PassingData.RData')
# w1Plays = plays[plays$gameId %in% games[games$week == 1,'gameId'],]
# w2Plays = plays[plays$gameId %in% games[games$week == 2,'gameId'],]
# w3Plays = plays[plays$ga... |
# 1.0 Loading Libraries ---------------------------------------------------
library(shiny)
library(argonR)
library(argonDash)
# library(tidyverse)
library(shinycssloaders)
library(shinyWidgets)
library(tidyverse)
library(readxl)
# library(pander)
library(highcharter)
library(DT)
# 1.1 Loading Data ----------... | /global.R | no_license | rzezela77/MFL_project | R | false | false | 3,921 | r |
# 1.0 Loading Libraries ---------------------------------------------------
library(shiny)
library(argonR)
library(argonDash)
# library(tidyverse)
library(shinycssloaders)
library(shinyWidgets)
library(tidyverse)
library(readxl)
# library(pander)
library(highcharter)
library(DT)
# 1.1 Loading Data ----------... |
## ----echo = FALSE, message = FALSE--------------------------------------------
library(knitr)
library(kableExtra)
library(TestDesign)
constraints_science_data[is.na(constraints_science_data)] <- ""
constraints_reading_data[is.na(constraints_reading_data)] <- ""
constraints_fatigue_data[is.na(constraints_fatigue_data... | /TestDesign/inst/doc/constraints.R | no_license | akhikolla/TestedPackages-NoIssues | R | false | false | 6,980 | r | ## ----echo = FALSE, message = FALSE--------------------------------------------
library(knitr)
library(kableExtra)
library(TestDesign)
constraints_science_data[is.na(constraints_science_data)] <- ""
constraints_reading_data[is.na(constraints_reading_data)] <- ""
constraints_fatigue_data[is.na(constraints_fatigue_data... |
#' crypto_correlation
#'
#' Function to calculate the correlation between two crypto currencies
#'
#' This function is designed to calcualte the correlation between two cryptocurrencies in a given timeframe
#'
#' @param firstDay first day to analyse in dd/mm/yyyy format
#' @param lastDay last day to analyse in dd/mm/yy... | /CryptoShiny/R/crypto_correlation.R | permissive | fernandopf/ThinkRProject | R | false | false | 1,016 | r | #' crypto_correlation
#'
#' Function to calculate the correlation between two crypto currencies
#'
#' This function is designed to calcualte the correlation between two cryptocurrencies in a given timeframe
#'
#' @param firstDay first day to analyse in dd/mm/yyyy format
#' @param lastDay last day to analyse in dd/mm/yy... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/siber.MVN.R
\name{siber.MVN}
\alias{siber.MVN}
\title{Fit Bayesian bivariate normal distributions to each group in each community}
\usage{
siber.MVN(siber, parms, priors)
}
\arguments{
\item{siber}{a siber object as created by \code{\... | /man/siber.MVN.Rd | no_license | andrewcparnell/SIBER | R | false | false | 2,246 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/siber.MVN.R
\name{siber.MVN}
\alias{siber.MVN}
\title{Fit Bayesian bivariate normal distributions to each group in each community}
\usage{
siber.MVN(siber, parms, priors)
}
\arguments{
\item{siber}{a siber object as created by \code{\... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/model.R
\name{cmdstan_model}
\alias{cmdstan_model}
\title{Create a new CmdStanModel object}
\usage{
cmdstan_model(stan_file, compile = TRUE, ...)
}
\arguments{
\item{stan_file}{The path to a \code{.stan} file containing a Stan program. The
he... | /man/cmdstan_model.Rd | permissive | spinkney/cmdstanr | R | false | true | 4,411 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/model.R
\name{cmdstan_model}
\alias{cmdstan_model}
\title{Create a new CmdStanModel object}
\usage{
cmdstan_model(stan_file, compile = TRUE, ...)
}
\arguments{
\item{stan_file}{The path to a \code{.stan} file containing a Stan program. The
he... |
### Model 1
# a ~ Cue
#
### modelSpec is a list containing:
# 1. The parameters to fit, and the factors they depend on
# 2. constants in the model
# 3. The factors from (1), and their levels
modelSpec = list('variablePars'=list('B' = 1,
't0' = 1,
... | /analysis/models/old_models/modelracingWaldAccAdvantagesU.R | permissive | StevenM1/RLDDM | R | false | false | 2,462 | r | ### Model 1
# a ~ Cue
#
### modelSpec is a list containing:
# 1. The parameters to fit, and the factors they depend on
# 2. constants in the model
# 3. The factors from (1), and their levels
modelSpec = list('variablePars'=list('B' = 1,
't0' = 1,
... |
##' Compute the F score, max diff ratio difference.
##' @title F score computation
##' @param geno.df a data.frame of one row with the genotype information for each sample.
##' @param tre.dist a distance object from the transcript relative expression.
##' @param tre.df a data.frame with the transcript relative expressi... | /R/compFscore.R | no_license | DuyDN/sQTLseekeR | R | false | false | 1,788 | r | ##' Compute the F score, max diff ratio difference.
##' @title F score computation
##' @param geno.df a data.frame of one row with the genotype information for each sample.
##' @param tre.dist a distance object from the transcript relative expression.
##' @param tre.df a data.frame with the transcript relative expressi... |
#' AI Platform Training & Prediction API
#' An API to enable creating and using machine learning models.
#'
#' Auto-generated code by googleAuthR::gar_create_api_skeleton
#' at 2022-07-13 10:40:00
#' filename: /Users/justin/Sync/projects/github.com/justinjm/autoGoogleAPI/googlemlv1.auto/R/ml_functions.R
#' api_json: ... | /googlemlv1.auto/R/ml_functions.R | no_license | justinjm/autoGoogleAPI | R | false | false | 60,402 | r | #' AI Platform Training & Prediction API
#' An API to enable creating and using machine learning models.
#'
#' Auto-generated code by googleAuthR::gar_create_api_skeleton
#' at 2022-07-13 10:40:00
#' filename: /Users/justin/Sync/projects/github.com/justinjm/autoGoogleAPI/googlemlv1.auto/R/ml_functions.R
#' api_json: ... |
require(ggplot2)
require(shiny)
require(dplyr)
require(wordcloud)
# Load the dataset
loadData <- function() {
maintable<- read.csv("./data/maintable.csv")
popullariteti <- read.csv("./data/popullariteti.csv")
wordcloud <- read.csv("./data/wordcloud.csv")
df <- list(maintable, popullariteti, wordcloud)
return... | /server.R | no_license | endri81/albaniannames | R | false | false | 5,117 | r | require(ggplot2)
require(shiny)
require(dplyr)
require(wordcloud)
# Load the dataset
loadData <- function() {
maintable<- read.csv("./data/maintable.csv")
popullariteti <- read.csv("./data/popullariteti.csv")
wordcloud <- read.csv("./data/wordcloud.csv")
df <- list(maintable, popullariteti, wordcloud)
return... |
testlist <- list(Rs = numeric(0), atmp = numeric(0), relh = numeric(0), temp = c(8.5728629954997e-312, 1.56898424065867e+82, 8.96970809549085e-158, -1.3258495253834e-113, 2.79620616433656e-119, -6.80033518839696e+41, 2.68298522855314e-211, 1444042902784.06, 6.68889884134308e+51, -4.05003163986346e-308, -3.526018204... | /meteor/inst/testfiles/ET0_Makkink/AFL_ET0_Makkink/ET0_Makkink_valgrind_files/1615855020-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 932 | r | testlist <- list(Rs = numeric(0), atmp = numeric(0), relh = numeric(0), temp = c(8.5728629954997e-312, 1.56898424065867e+82, 8.96970809549085e-158, -1.3258495253834e-113, 2.79620616433656e-119, -6.80033518839696e+41, 2.68298522855314e-211, 1444042902784.06, 6.68889884134308e+51, -4.05003163986346e-308, -3.526018204... |
backProp <- function(y, layers, alpha){
#alpha <- cnn$lrate
outlayer <- layers[[length(layers)]]
#y <- cnn$y
outlayer <- updateWeight(outlayer, y, alpha)
layers[[length(layers)]] <- outlayer
for(i in (length(layers) - 1):1){
print(layers[[i]]$type)
layers[[i]] <- update... | /backProp.R | no_license | LinHungShi/ConvolutionalNeuralNetwork | R | false | false | 418 | r | backProp <- function(y, layers, alpha){
#alpha <- cnn$lrate
outlayer <- layers[[length(layers)]]
#y <- cnn$y
outlayer <- updateWeight(outlayer, y, alpha)
layers[[length(layers)]] <- outlayer
for(i in (length(layers) - 1):1){
print(layers[[i]]$type)
layers[[i]] <- update... |
##R script to obtain counts per transcript when reads have been mapped to cDNAs
##searches working directory for .sam files and summarizes them.
#BEFORE running the lines below change the working directory to
#the directory with sam files. If your files end in something
#other than ".sam" change the command b... | /RNAseq/scripts/sam2counts.R | permissive | iamciera/Scripts-and-Protocols | R | false | false | 2,028 | r | ##R script to obtain counts per transcript when reads have been mapped to cDNAs
##searches working directory for .sam files and summarizes them.
#BEFORE running the lines below change the working directory to
#the directory with sam files. If your files end in something
#other than ".sam" change the command b... |
\name{nicheoverlap}
\Rdversion{1.1}
\alias{nicheoverlap}
\alias{nichedispl}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Metrics to compare pairs of resource niches
}
\description{
Functions \code{nicheoverlap} and \code{nichedispl} compute the overlap and centroid distance between pairs of re... | /man/nicheoverlap.Rd | no_license | HaleyArnold33/indicspecies | R | false | false | 7,090 | rd | \name{nicheoverlap}
\Rdversion{1.1}
\alias{nicheoverlap}
\alias{nichedispl}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Metrics to compare pairs of resource niches
}
\description{
Functions \code{nicheoverlap} and \code{nichedispl} compute the overlap and centroid distance between pairs of re... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sstable.R
\name{sstable.ae}
\alias{sstable.ae}
\title{Create an adverse event summary table}
\usage{
sstable.ae(ae_data, fullid_data, id.var, aetype.var, grade.var = NULL,
arm.var, digits = 0, test = TRUE, pdigits = 3, pcutoff = 0.001,
ch... | /man/sstable.ae.Rd | no_license | choisy/C306 | R | false | true | 2,317 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sstable.R
\name{sstable.ae}
\alias{sstable.ae}
\title{Create an adverse event summary table}
\usage{
sstable.ae(ae_data, fullid_data, id.var, aetype.var, grade.var = NULL,
arm.var, digits = 0, test = TRUE, pdigits = 3, pcutoff = 0.001,
ch... |
source("spatcontrol/spatcontrol.R",local=TRUE,chdir=TRUE)
db<-read.csv("OriginalDataPaucarpata.csv")
db<-set_to(db,init=c("NULL"),final=0)
db<-db[which(!is.na(db$easting)),]
db<-changeNameCol(db,"easting","X") # from "easting" to "X"
db<-changeNameCol(db,"northing","Y")
db<-changeNameCol(db,"infested","positive")
db<-c... | /example_generation.R | no_license | JavierQC/spatcontrol | R | false | false | 1,476 | r | source("spatcontrol/spatcontrol.R",local=TRUE,chdir=TRUE)
db<-read.csv("OriginalDataPaucarpata.csv")
db<-set_to(db,init=c("NULL"),final=0)
db<-db[which(!is.na(db$easting)),]
db<-changeNameCol(db,"easting","X") # from "easting" to "X"
db<-changeNameCol(db,"northing","Y")
db<-changeNameCol(db,"infested","positive")
db<-c... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/paws.ecr_operations.R
\name{create_repository}
\alias{create_repository}
\title{Creates an image repository}
\usage{
create_repository(repositoryName, tags = NULL)
}
\arguments{
\item{repositoryName}{[required] The name to use for the reposit... | /service/paws.ecr/man/create_repository.Rd | permissive | CR-Mercado/paws | R | false | true | 990 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/paws.ecr_operations.R
\name{create_repository}
\alias{create_repository}
\title{Creates an image repository}
\usage{
create_repository(repositoryName, tags = NULL)
}
\arguments{
\item{repositoryName}{[required] The name to use for the reposit... |
# This script can be used to replicate the analysis undertaken in the summer
# project "Where are the missing grasses?" based at RBG Kew in summer 2016.
#
# For a full explanation of the script and the methods it employs, as well as
# how to use it yourself please see the readme in this repository.
# ... | /Support/Data_Processing/author_method.R | no_license | fdbesanto2/kew_grasses | R | false | false | 3,683 | r | # This script can be used to replicate the analysis undertaken in the summer
# project "Where are the missing grasses?" based at RBG Kew in summer 2016.
#
# For a full explanation of the script and the methods it employs, as well as
# how to use it yourself please see the readme in this repository.
# ... |
#-------------------------------------- HEADER --------------------------------------------#
#' @title Distributed Student's t-Test
#' @description Computes one and two sample t-tests on vectors of data
#' @details If paired is TRUE then both x and y must be specified and they must be the same length. Missing values ar... | /R/ds.tTest.R | no_license | paularaissa/distStatsClient | R | false | false | 5,744 | r | #-------------------------------------- HEADER --------------------------------------------#
#' @title Distributed Student's t-Test
#' @description Computes one and two sample t-tests on vectors of data
#' @details If paired is TRUE then both x and y must be specified and they must be the same length. Missing values ar... |
###########################################################################################
#1) Первая часть — очистка рабочего пространства, задание раб директории
setwd("/home/nazarov/02-fmlab.hse.ru/ТЗ до 29.07.2015/With zero/")
#setwd("J:/12 - ЛАФР/02 - Декомпозиция")
#clear working environment
rm(list=ls())
... | /03 - данные с нулями/russia_zero.R | no_license | nicknazarov/02-fmlab.hse.ru | R | false | false | 8,155 | r |
###########################################################################################
#1) Первая часть — очистка рабочего пространства, задание раб директории
setwd("/home/nazarov/02-fmlab.hse.ru/ТЗ до 29.07.2015/With zero/")
#setwd("J:/12 - ЛАФР/02 - Декомпозиция")
#clear working environment
rm(list=ls())
... |
require(stringr)
require(plyr)
require(ggplot2)
require(mboost)
require(randomForest)
## hey!
## Load Data
sampleSub <- read.csv(file="sample_submission_file.csv",
stringsAsFactors=F)
train <- read.delim(file="train.tsv",
stringsAsFactors=FALSE,
fill=FAL... | /final-project.r | no_license | littlemerman/pproject | R | false | false | 2,518 | r | require(stringr)
require(plyr)
require(ggplot2)
require(mboost)
require(randomForest)
## hey!
## Load Data
sampleSub <- read.csv(file="sample_submission_file.csv",
stringsAsFactors=F)
train <- read.delim(file="train.tsv",
stringsAsFactors=FALSE,
fill=FAL... |
\name{Many simple quantile regressions using logistic regressions}
\alias{logiquant.regs}
\title{
Many simple quantile regressions using logistic regressions.
}
\description{
Many simple quantile regressions using logistic regressions.
}
\usage{
logiquant.regs(target, dataset, logged = FALSE)
}
\argume... | /man/logiquant.regs.Rd | no_license | cran/MXM | R | false | false | 1,812 | rd | \name{Many simple quantile regressions using logistic regressions}
\alias{logiquant.regs}
\title{
Many simple quantile regressions using logistic regressions.
}
\description{
Many simple quantile regressions using logistic regressions.
}
\usage{
logiquant.regs(target, dataset, logged = FALSE)
}
\argume... |
rm(list = ls())
#Load Libraries
x = c('ggplot2', 'corrgram', 'DMwR', 'caret', 'randomForest', 'unbalanced', 'C50', 'dummies',
'e1071', 'Information','MASS','rpart', 'gbm', 'ROSE')
#install.packages(x)
lapply(x, require, character.only = TRUE)
rm(x)
library(ggplot2)
#Importing the dataset
setwd('C:/Users/chai... | /Project.r | no_license | chaitu009/Telecom-Customer-Churn | R | false | false | 4,643 | r | rm(list = ls())
#Load Libraries
x = c('ggplot2', 'corrgram', 'DMwR', 'caret', 'randomForest', 'unbalanced', 'C50', 'dummies',
'e1071', 'Information','MASS','rpart', 'gbm', 'ROSE')
#install.packages(x)
lapply(x, require, character.only = TRUE)
rm(x)
library(ggplot2)
#Importing the dataset
setwd('C:/Users/chai... |
library(knitr)
opts_chunk$set(prompt=TRUE, eval=FALSE, tidy=FALSE, strip.white=FALSE, comment=NA, highlight=FALSE, message=FALSE, warning=FALSE, size='scriptsize', fig.width=6, fig.height=5)
options(width=60, dev='pdf')
options(digits=3)
thm <- knit_theme$get("acid")
knit_theme$set(thm)
# Define a function with two ar... | /functions.R | no_license | Williamqn/lecture_slides | R | false | false | 24,645 | r | library(knitr)
opts_chunk$set(prompt=TRUE, eval=FALSE, tidy=FALSE, strip.white=FALSE, comment=NA, highlight=FALSE, message=FALSE, warning=FALSE, size='scriptsize', fig.width=6, fig.height=5)
options(width=60, dev='pdf')
options(digits=3)
thm <- knit_theme$get("acid")
knit_theme$set(thm)
# Define a function with two ar... |
\name{transparentColorBase}
\alias{transparentColorBase}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Set Transparancey in Base Graphics}
\description{Setting transparency in base graphics is not as easy as in
\code{Lattice}, so here's a little functon to help.}
\usage{
transparentColorBas... | /man/transparentColorBase.Rd | no_license | cran/sampSurf | R | false | false | 1,219 | rd | \name{transparentColorBase}
\alias{transparentColorBase}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Set Transparancey in Base Graphics}
\description{Setting transparency in base graphics is not as easy as in
\code{Lattice}, so here's a little functon to help.}
\usage{
transparentColorBas... |
#---
# Author: "Ian Hinds"
# Date: 2020-08-13
# Purpose: Day 7 assignment: joining, pivots, splits, plots
#1
# Make a faceted plot of the cumulative cases & deaths by USA region. Your x axis is date, y axis is value/count. Join and pivot the covid 19 data.
#read covid data
library(tidyverse)
url = 'https://raw.github... | /R/ianhinds-day-07.R | no_license | Hindstein/geog176A-daily-exercises | R | false | false | 1,293 | r | #---
# Author: "Ian Hinds"
# Date: 2020-08-13
# Purpose: Day 7 assignment: joining, pivots, splits, plots
#1
# Make a faceted plot of the cumulative cases & deaths by USA region. Your x axis is date, y axis is value/count. Join and pivot the covid 19 data.
#read covid data
library(tidyverse)
url = 'https://raw.github... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/runRppsc.R
\name{runRppsc}
\alias{runRppsc}
\title{launch Rppsc shiny app}
\usage{
runRppsc()
}
\value{
null
}
\description{
A function launches the Rppsc Shiny app that allows the user to use the features
of Rppsc package in an interactive w... | /man/runRppsc.Rd | permissive | dxjasmine/Rppsc | R | false | true | 366 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/runRppsc.R
\name{runRppsc}
\alias{runRppsc}
\title{launch Rppsc shiny app}
\usage{
runRppsc()
}
\value{
null
}
\description{
A function launches the Rppsc Shiny app that allows the user to use the features
of Rppsc package in an interactive w... |
# Enter your code here. Read input from STDIN. Print output to STDOUT
array <- read.table(file = "stdin", header = F, fill = T, sep = " ")
revArray <- rev(array[2,]) #reverse values
write.table(revArray, row.names = F, col.names = F) #remove overhead variable and row names for printing
| /[Easy] Arrays - DS.R | no_license | fardeen-ahmed/HackerRank | R | false | false | 287 | r | # Enter your code here. Read input from STDIN. Print output to STDOUT
array <- read.table(file = "stdin", header = F, fill = T, sep = " ")
revArray <- rev(array[2,]) #reverse values
write.table(revArray, row.names = F, col.names = F) #remove overhead variable and row names for printing
|
# ##############################################################################
# Author: Georgios Kampolis
#
# Description: Creates boxplots to explore seasonality of the data set.
#
# ##############################################################################
wind %<>% mutate(year = as.factor(year(dateTime)),
... | /scripts/3_3EDABoxPlot.R | permissive | gkampolis/ChilWind | R | false | false | 1,675 | r | # ##############################################################################
# Author: Georgios Kampolis
#
# Description: Creates boxplots to explore seasonality of the data set.
#
# ##############################################################################
wind %<>% mutate(year = as.factor(year(dateTime)),
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/characterise_episodes.R
\name{episode_varacity}
\alias{episode_varacity}
\title{Summarise Non-Verifiable Episodes}
\usage{
episode_varacity(df)
}
\arguments{
\item{df}{the episode table returned from \code{\link{characterise_episodes}}}
}
\va... | /man/episode_varacity.Rd | no_license | CC-HIC/inspectEHR | R | false | true | 478 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/characterise_episodes.R
\name{episode_varacity}
\alias{episode_varacity}
\title{Summarise Non-Verifiable Episodes}
\usage{
episode_varacity(df)
}
\arguments{
\item{df}{the episode table returned from \code{\link{characterise_episodes}}}
}
\va... |
load(file="data/trips.20160613_19.all.RData")
univ
grouped <- univ1month %>% group_by(px4,py4) %>% summarise( meantip = mean(tip_amount), meanhpay = mean(hpay), medianhpay=median(hpay), highRate= sum(isHigh)/ n(), n = n(), pa = min(pickup_latitude), po = min(pickup_longitude) ) %>% filter( n >= 200 ) %>% mutate( hpay... | /R/EDA-visualize_tip.R | no_license | Sapphirine/Tip_Prediction_and_GPS_Noise_Modeling_on_NYC_Taxi_Dataset | R | false | false | 1,127 | r | load(file="data/trips.20160613_19.all.RData")
univ
grouped <- univ1month %>% group_by(px4,py4) %>% summarise( meantip = mean(tip_amount), meanhpay = mean(hpay), medianhpay=median(hpay), highRate= sum(isHigh)/ n(), n = n(), pa = min(pickup_latitude), po = min(pickup_longitude) ) %>% filter( n >= 200 ) %>% mutate( hpay... |
require("project.init")
require("Seurat")
require("gplots")
require(methods)
require(pheatmap)
require(gdata)
require(enrichR) #devtools::install_github("definitelysean/enrichR")
out <- "20_AggregatedLists/"
dir.create(dirout(out))
project.init2("cll-time_course")
atacRes <- list()
cell <- "Bcell"
for(cell in c("Bce... | /src/single_cell_RNA/20_AggregateLists_Enrichr.R | no_license | nattzy94/cll-ibrutinib_time | R | false | false | 4,695 | r | require("project.init")
require("Seurat")
require("gplots")
require(methods)
require(pheatmap)
require(gdata)
require(enrichR) #devtools::install_github("definitelysean/enrichR")
out <- "20_AggregatedLists/"
dir.create(dirout(out))
project.init2("cll-time_course")
atacRes <- list()
cell <- "Bcell"
for(cell in c("Bce... |
# Emma Peltomaa
# 18.11.2018
# Creating two datasets, they are downloaded from here: https://archive.ics.uci.edu/ml/datasets/Student+Performance
# Reading the datasets
math <- read.table("student-mat.csv", sep=";", header=TRUE)
por <- read.table("student-por.csv", sep=";", header=TRUE)
# Dimensions of the datasets
di... | /data/create_alc.R | no_license | peempe/IODS-project | R | false | false | 2,247 | r | # Emma Peltomaa
# 18.11.2018
# Creating two datasets, they are downloaded from here: https://archive.ics.uci.edu/ml/datasets/Student+Performance
# Reading the datasets
math <- read.table("student-mat.csv", sep=";", header=TRUE)
por <- read.table("student-por.csv", sep=";", header=TRUE)
# Dimensions of the datasets
di... |
## ----sfs----------------------------------------------------------------------
sfs <- c(112, 57, 24, 34, 16, 29, 8, 10, 15)
## ----model setup--------------------------------------------------------------
library(coala)
model <- coal_model(10, 50) +
feat_mutation(par_prior("theta", runif(1, 1, 5))) +
sumstat_sfs... | /fuzzedpackages/coala/inst/doc/coala-abc.R | no_license | akhikolla/testpackages | R | false | false | 975 | r | ## ----sfs----------------------------------------------------------------------
sfs <- c(112, 57, 24, 34, 16, 29, 8, 10, 15)
## ----model setup--------------------------------------------------------------
library(coala)
model <- coal_model(10, 50) +
feat_mutation(par_prior("theta", runif(1, 1, 5))) +
sumstat_sfs... |
testlist <- list(A = structure(c(2.31584307509357e+77, 1.19893625614874e+297, 1.22810536108214e+146, 4.12396251261199e-221, 0, 0, 0), .Dim = c(1L, 7L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_rows,testlist)
str(result) | /multivariance/inst/testfiles/match_rows/AFL_match_rows/match_rows_valgrind_files/1613109058-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 257 | r | testlist <- list(A = structure(c(2.31584307509357e+77, 1.19893625614874e+297, 1.22810536108214e+146, 4.12396251261199e-221, 0, 0, 0), .Dim = c(1L, 7L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_rows,testlist)
str(result) |
#' Calcula R efetivo sobre a estimativas de nowcasting retornadas pela função NobBS::NobBS
#'
#' @param ncasos vetor de número de novos casos
#' @param dia0 dia zero
#' @param delay atraso
#' @param datas vetor de datas dos novos casos
#' @export
#'
re.com.data <- function(ncasos, datas, dia0 = min(datas), delay = 5) {... | /R/Re.com.data.R | permissive | covid19br/now_fcts | R | false | false | 754 | r | #' Calcula R efetivo sobre a estimativas de nowcasting retornadas pela função NobBS::NobBS
#'
#' @param ncasos vetor de número de novos casos
#' @param dia0 dia zero
#' @param delay atraso
#' @param datas vetor de datas dos novos casos
#' @export
#'
re.com.data <- function(ncasos, datas, dia0 = min(datas), delay = 5) {... |
library(Rllvm)
mods = lapply(bcs, readBitcode)
ins = lapply(mods, function(x) unlist(getInstructions(x)))
alloc = lapply(ins, function(i) i[ sapply(i, function(x) is(x, "CallInst") && is((cf <- getCalledFunction(x)), "Function") && grepl("^Rf_allocVector", Rllvm::getName(cf)) ) ])
ualloc = unlist(alloc)
k = sapply(... | /CRAN/listAllocWithDifferentLengths.R | no_license | duncantl/NativeCodeAnalysis | R | false | false | 2,806 | r | library(Rllvm)
mods = lapply(bcs, readBitcode)
ins = lapply(mods, function(x) unlist(getInstructions(x)))
alloc = lapply(ins, function(i) i[ sapply(i, function(x) is(x, "CallInst") && is((cf <- getCalledFunction(x)), "Function") && grepl("^Rf_allocVector", Rllvm::getName(cf)) ) ])
ualloc = unlist(alloc)
k = sapply(... |
####### read in data from the coso geothermal field and plot
###### using swig
options(demo.ask=FALSE)
data("GH")
#########
####
STDLAB = c("DONE", "zoom in", "zoom out", "refresh", "restore",
"XTR", "SPEC", "SGRAM" ,"3COMP", "FILT", "Pinfo")
###sel = which(GH$COMPS=="V")
gsel = getvertsorder(GH$pickfile, ... | /demo/COSO.R | no_license | cran/RSEIS | R | false | false | 653 | r |
####### read in data from the coso geothermal field and plot
###### using swig
options(demo.ask=FALSE)
data("GH")
#########
####
STDLAB = c("DONE", "zoom in", "zoom out", "refresh", "restore",
"XTR", "SPEC", "SGRAM" ,"3COMP", "FILT", "Pinfo")
###sel = which(GH$COMPS=="V")
gsel = getvertsorder(GH$pickfile, ... |
# Test download, building and querying random seq.files from GenBank
# Vars
n <- 2 # n per genbank type
wd <- '.'
restez_lib_path <- '~/Coding/restez'
to_download <- TRUE
to_build <- TRUE
# restez setup
devtools::load_all(restez_lib_path)
restez_path_set(wd)
if (to_download) {
# delete any old files
db_delete(ev... | /other/random_file_tester.R | permissive | ropensci/restez | R | false | false | 3,141 | r | # Test download, building and querying random seq.files from GenBank
# Vars
n <- 2 # n per genbank type
wd <- '.'
restez_lib_path <- '~/Coding/restez'
to_download <- TRUE
to_build <- TRUE
# restez setup
devtools::load_all(restez_lib_path)
restez_path_set(wd)
if (to_download) {
# delete any old files
db_delete(ev... |
library(devtools)
# resubmit the source package to cran
if (.Platform$OS.type == "windows") {
setwd("C:/Academia/Cornell/Research/Conditional Mean Independence")
} else {
setwd("~")
}
submit_cran("CMDMeasure")
| /dev/resubmit_package.R | no_license | zejin/CMDMeasure | R | false | false | 217 | r | library(devtools)
# resubmit the source package to cran
if (.Platform$OS.type == "windows") {
setwd("C:/Academia/Cornell/Research/Conditional Mean Independence")
} else {
setwd("~")
}
submit_cran("CMDMeasure")
|
## Customer reviews from IMDB on the movie "AQUAMAN" and performed wordcloud and Sentimental analysis on the same
library(rvest)
library(XML)
library(magrittr)
library(tm)
library(wordcloud)
library(wordcloud2)
library(syuzhet)
library(lubridate)
library(ggplot2)
library(scales)
library(reshape2)
library(... | /IMDB.R | no_license | pratiksawant24/Excelr-Assignments | R | false | false | 4,073 | r | ## Customer reviews from IMDB on the movie "AQUAMAN" and performed wordcloud and Sentimental analysis on the same
library(rvest)
library(XML)
library(magrittr)
library(tm)
library(wordcloud)
library(wordcloud2)
library(syuzhet)
library(lubridate)
library(ggplot2)
library(scales)
library(reshape2)
library(... |
seed <- 273
log.wt <- 0.0
penalty <- 2.8115950178536287e-8
intervals.send <- c()
intervals.recv <- c(56, 112, 225, 450, 900, 1800, 3600, 7200, 14400, 28800, 57600, 115200, 230400, 460800, 921600, 1843200, 3686400, 7372800, 14745600, 29491200, 58982400)
dev.null <- 358759.0022669336
df.null <- 35567
dev.resid <- 224861.... | /analysis/boot/boot273.R | no_license | patperry/interaction-proc | R | false | false | 3,743 | r | seed <- 273
log.wt <- 0.0
penalty <- 2.8115950178536287e-8
intervals.send <- c()
intervals.recv <- c(56, 112, 225, 450, 900, 1800, 3600, 7200, 14400, 28800, 57600, 115200, 230400, 460800, 921600, 1843200, 3686400, 7372800, 14745600, 29491200, 58982400)
dev.null <- 358759.0022669336
df.null <- 35567
dev.resid <- 224861.... |
\name{lmImpute}
\alias{lmImpute}
\title{Locally Weighted Linear Imputation}
\usage{
lmImpute(x, ...)
}
\arguments{
\item{x}{a data frame or matrix where each row represents
a different record}
\item{...}{additional parameters passed to locfit}
}
\description{
Fill missing values in a column by running a loca... | /man/lmImpute.Rd | no_license | JMoon1/imputation | R | false | false | 531 | rd | \name{lmImpute}
\alias{lmImpute}
\title{Locally Weighted Linear Imputation}
\usage{
lmImpute(x, ...)
}
\arguments{
\item{x}{a data frame or matrix where each row represents
a different record}
\item{...}{additional parameters passed to locfit}
}
\description{
Fill missing values in a column by running a loca... |
setMethod("[", signature(x="CCProfile", i="index"),
function(x, i)
{
if (is.character(i))
{
if (length(names(x@sequences)) < 1 ||
any(is.na(names(x@sequences))))
stop("missing names for subsetting\n")
else
i1 <- which(names(... | /R/access-methods.R | no_license | UBod/procoil | R | false | false | 1,106 | r | setMethod("[", signature(x="CCProfile", i="index"),
function(x, i)
{
if (is.character(i))
{
if (length(names(x@sequences)) < 1 ||
any(is.na(names(x@sequences))))
stop("missing names for subsetting\n")
else
i1 <- which(names(... |
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