## Example of a CLT demonstration.

f <- tempfile()                         # gcanvas uses file, not url
makePlot <- function(h,...) {
  require(canvas, quietly=TRUE, warn=FALSE)
  n <- min(as.numeric(svalue(sampleSize)), 500)
  m <- min(as.numeric(svalue(replicates)), 500)
  cmd <- pops[[svalue(population, index=TRUE)]]
  cmd$n <- n * m
  x <- matrix($cmd, cmd[-(1:2)]), nrow=n)
  xbars <- apply(x, 2, function(x) mean(x))
  canvas(f, width=500, height=400, bg="#ffffff")
  plot(density(xbars), main=sprintf("Population: %s, n: %s", svalue(population), svalue(sampleSize)))
  svalue(p) <- f

## Begin layout
w <- gwindow("CLT example")
g <- ggroup(horizontal=FALSE, cont=w)

if(!require(canvas)) {
  glabel("This demo requires the canvas package", cont=g)
} else {

  l <- glabel("Distribution of xbar, the sample mean.", cont = g)
  ## main widget is canvas
  p <- gcanvas(width=500, height=400, cont = g)
  pops <- list("rnorm(n,0,1)" = list(cmd="rnorm", tooltip="Normal", mean=0, sd=1),
               "rexp(n)" = list(cmd="rexp", tooltip="Skewed"),
               "rt(n, df=3)" = list(cmd="rt",tooltip="Symmetric, long tailed", df=3),
               "rt(n, df=30)" = list(cmd="rt", tooltip="Symmetric, some tail", df=30),
               "runif(n)" = list(cmd="runif", tooltip="Short tail"),
               "rlnorm(n)" = list(cmd="rlnorm", tooltip="Very skewed")
  popsdf <- data.frame(names(pops),rep("plot",length(pops)),
                       tooltips=sapply(pops,function(i) i$tooltip), stringsAsFactors=FALSE)
  tbl <- glayout(cont = g)
  tbl[1,1] <- "n (sample size)"
  tbl[1,2] <- (sampleSize <- gedit("10", cont = tbl, coerce.with="as.numeric"))
  tbl[2,1] <- "Population:"
  tbl[2,2] <- (population <- gcombobox(popsdf,
                                       editable=FALSE, cont=tbl))
  tbl[3,1] <- "Replicates"
  tbl[3,2] <- (replicates <- gslider(from=10, to=200, by=1, value=50, cont=tbl))
  g1 <- ggroup(cont = g)
  b <- gbutton("plot", cont = g1, handler=makePlot)
  helpButton <- gbutton("help", cont = g1, handler=function(h,...) {
    w1 <- gwindow("Help with CLT demo", parent=w)
    g <- ggroup(cont = w1, horizontal=FALSE)
    ghtml(paste("<h1>CLT Example</h1>",
                "Demonstrates the Central Limit Theorem, which says the CDF of the sample mean",
                "of a random sample",
                "of <i>n</i> data points converges to that of the normal distribution as",
                "<i>n</i> goes to infinity. This shows a density estimate, so it is not quite the same for discrete",
                "populations, but still illustrates the point.",
                "<li>Set the <b>sample size</b> by adjusting the value of <i>n</i>.</li>",
                "<li>Set the <b>population</b> from one of the set ones.",
                "The value <i>n</i>can be used as a parameter.</li>",
                "<li>Adjust the number of <b>replicates</b> if desired.</li>",
                "Click the <b>plot</b> button to update the plot",
                sep=" "), cont = g, expand=TRUE)
    gseparator(cont = g)
    gbutton("dismiss", cont = g, handler=function(h,...) {
    visible(w1) <- TRUE

## show off
gstatusbar("Powered by RApache and gWidgetsWWW", cont = w)
visible(w) <- TRUE

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gWidgetsWWW documentation built on May 2, 2019, 4:47 p.m.