dsparks

aPlotFunction <- function(hh, ss, sz){
  zp1 <- qplot(data = cars, x = dist, y = speed,
               colour = I(hsv(hh/255, 1, 1)),
               shape = I(ss),
               size = I(sz))
  print(zp1 + theme_bw())
}

manipulate(
  aPlotFunction(hh, ss, sz),

withr

library(shiny)
library(datasets)
Logged = FALSE;
PASSWORD <- data.frame(Brukernavn = "withr", Passord = "25d55ad283aa400af464c76d713c07ad")
# Define server logic required to summarize and view the selected dataset
shinyServer(function(input, output) {
  source("www/Login.R",  local = TRUE)
  
  observe({
    if (USER$Logged == TRUE) {

kerimdzhanov

/**
 * Get a random floating point number between `min` and `max`.
 * 
 * @param {number} min - min number
 * @param {number} max - max number
 * @return {number} a random floating point number
 */
function getRandomFloat(min, max) {
  return Math.random() * (max - min) + min;
}

mrdwab

stratified <- function(df, group, size, select = NULL, 
                       replace = FALSE, bothSets = FALSE) {
  if (is.null(select)) {
    df <- df
  } else {
    if (is.null(names(select))) stop("'select' must be a named list")
    if (!all(names(select) %in% names(df)))
      stop("Please verify your 'select' argument")
    temp <- sapply(names(select),
                   function(x) df[[x]] %in% select[[x]])

jcheng5

# Nothing to see here
shinyServer(function(input, output) {
})

jbryer

#List of most used R packages that we wish to install.
libraries = c('cacheSweave', 'Deducer', 'devtools', 'doBy', 'foreign', 'gdata', 
			  'ggplot2', 'Hmisc', 'JGR', 'lubridate', 'maps', 'mapdata', 'mapproj', 
			  'maptools', 'proto', 'psych', 'R2wd', 'RCurl', 'reshape', 
			  'RODBC', 'roxygen2', 'seqinr', 'sm', 'sp', 'sqldf', 'survey', 
			  'WriteXLS', 'XML', 'xtable')

#We will install packages from the main CRAN site
repos = 'http://cran.r-project.org'
#Site provides some prebuilt binaries for Windows

johncolby

library(plyr)
library(ggplot2)

# Simulate data
numSubs = 40

x = runif(numSubs, 0, 30)
x = c(x, x + abs(rnorm(numSubs, 2)))
y = 2 + x - 0.02*x^2 + rnorm(2*numSubs, 0, 1)

sebleier

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