Plot sampling distribution of mean or other sample statistic.
The function sampvals generates the data. A density plot
of a normal probability plot is provided, for one or mare sample
sizes. For a density plot, the density estimate for the population
is superimposed in gray. For the normal probability plot, the
population plot is a dashed gray line. Default arguments give the
sampling distribution of the mean, for a distribution that is
mildly positively skewed.
sampdist(sampsize = c(3, 9, 30), seed = NULL, nsamp = 1000, FUN = mean,
sampvals = function(n) exp(rnorm(n, mean = 0.5, sd = 0.3)),
tck = NULL, plot.type = c("density", "qq"), layout = c(3, 1))sampvals |
Function that generates the data. For sampling from existing data values, this might be function that generates bootstrap samples. |
sampsize |
One or more sample sizes. A plot will be provided for each different sample size. |
seed |
Specify a seed if it is required to make the exact set(s) of sample values reproducible. |
nsamp |
Number of samples. |
FUN |
Function that calculates the sample statistic. |
plot.type |
Specify |
tck |
Tick size on lattice plots, by default 1, but 0.5 may be suitable for plots that are, for example, 50% of the default dimensions in each direction. |
layout |
Layout on page, e.g. |
Data frame
John Maindonald.
sampdist(plot.type="density")
sampdist(plot.type="qq")
## The function is currently defined as
function (sampsize = c(3, 9, 30), seed = NULL, nsamp = 1000, FUN = mean,
sampvals = function(n) exp(rnorm(n, mean = 0.5, sd = 0.3)),
tck = NULL, plot.type = c("density", "qq"), layout = c(3,
1))
{
if (!is.null(seed))
set.seed(seed)
ncases <- length(sampsize)
y <- sampvals(nsamp)
xlim = quantile(y, c(0.01, 0.99))
xlim <- xlim + c(-1, 1) * diff(xlim) * 0.1
samplingDist <- function(sampsize=3, nsamp=1000, FUN=mean)
apply(matrix(sampvals(sampsize*nsamp), ncol=sampsize), 1, FUN)
df <- data.frame(sapply(sampsize, function(x)samplingDist(x, nsamp=nsamp)))
names(df) <- paste("y", sampsize, sep="")
form <- formula(paste("~", paste(names(df), collapse="+")))
lab <- lapply(sampsize, function(x) substitute(A, list(A = paste(x))))
if (plot.type[1] == "density")
gph <- densityplot(form, data=df, layout = layout, outer=TRUE,
plot.points = FALSE, panel = function(x, ...) {
panel.densityplot(x, ..., col = "black")
panel.densityplot(y, col = "gray40", lty = 2,
...)
}, xlim = xlim, xlab = "", scales = list(tck = tck),
between = list(x = 0.5), strip = strip.custom(strip.names = TRUE,
factor.levels = as.expression(lab), var.name = "Sample size",
sep = expression(" = ")))
else if (plot.type[1] == "qq")
gph <- qqmath(form, data = df, layout = layout, plot.points = FALSE,
outer=TRUE,
panel = function(x, ...) {
panel.qqmath(x, ..., col = "black", alpha=0.5)
panel.qqmath(y, col = "gray40", lty = 2, type = "l",
...)
}, xlab = "", xlim = c(-3, 3), ylab = "", scales = list(tck = tck),
between = list(x = 0.5), strip = strip.custom(strip.names = TRUE,
factor.levels = as.expression(lab), var.name = "Sample size",
sep = expression(" = ")))
if (plot.type[1] %in% c("density", "qq"))
print(gph)
invisible(df)
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