qdist: Illustrated quantile calculations from distributions

In mosaic: Project MOSAIC Statistics and Mathematics Teaching Utilities

Illustrated quantile calculations from distributions

Description

Illustrated quantile calculations from distributions

Usage

qdist(
  dist = "norm",
  p,
  plot = TRUE,
  verbose = FALSE,
  invisible = FALSE,
  resolution = 500L,
  digits = 3L,
  xlim,
  ylim,
  return = c("values", "plot"),
  refinements = list(),
  ...
)

xqgamma(
  p,
  shape,
  rate = 1,
  scale = 1/rate,
  lower.tail = TRUE,
  log.p = FALSE,
  ...
)

xqt(p, df, ncp, lower.tail = TRUE, log.p = FALSE, ...)

xqchisq(p, df, ncp = 0, lower.tail = TRUE, log.p = FALSE, ...)

xqf(p, df1, df2, lower.tail = TRUE, log.p = FALSE, ...)

xqbinom(p, size, prob, lower.tail = TRUE, log.p = FALSE, ...)

xqpois(p, lambda, lower.tail = TRUE, log.p = FALSE, ...)

xqgeom(p, prob, lower.tail = TRUE, log.p = FALSE, ...)

xqnbinom(p, size, prob, mu, lower.tail = TRUE, log.p = FALSE, ...)

xqbeta(p, shape1, shape2, ncp = 0, lower.tail = TRUE, log.p = FALSE, ...)

Arguments

dist	a character description of a distribution, for example "norm", "t", or "chisq"
p	a vector of probabilities
plot	a logical indicating whether a plot should be created
verbose	a logical
invisible	a logical
resolution	number of points used for detecting discreteness and generating plots. The default value of 5000 should work well except for discrete distributions that have many distinct values, especially if these values are not evenly spaced.
digits	the number of digits desired
xlim	x limits. By default, these are chosen to show the central 99.8\ of the distribution.
ylim	y limits
return	If "plot", return a plot. If "values", return a vector of numerical values.
refinements	A list of refinements to the plot. See ggformula::gf_refine().
...	additional arguments, including parameters of the distribution and additional options for the plot. To help with name collisions (eg size for binomial distributions and shape for gamma distributions), argument names beginning plot_ will be renamed to remove plot_ and passed only to the plot. The unprefixed version will used as a parameter for the the distribution.
shape, scale	shape and scale parameters. Must be positive, scale strictly.
rate	an alternative way to specify the scale.
lower.tail	logical; if TRUE (default), probabilities are P[X \le x], otherwise, P[X > x].
log.p	A logical indicating whether probabilities should be returned on the log scale.
df	degrees of freedom (> 0, maybe non-integer). df = Inf is allowed.
ncp	non-centrality parameter \delta; currently except for rt(), only for abs(ncp) <= 37.62. If omitted, use the central t distribution.
df1, df2	degrees of freedom. Inf is allowed.
size	number of trials (zero or more).
prob	probability of success on each trial.
lambda	vector of (non-negative) means.
mu	alternative parametrization via mean: see ‘Details’.
shape1, shape2	non-negative parameters of the Beta distribution.

Details

The most general function is qdist which can work with any distribution for which a q-function exists. As a convenience, wrappers are provided for several common distributions.

Value

a vector of quantiles; a plot is printed as a side effect

Examples

qdist("norm", seq(.1, .9, by = 0.10), 
      title = "Deciles of a normal distribution", show.legend = FALSE,
      pattern = "rings")
xqnorm(seq(.2, .8, by = 0.20), mean = 100, sd = 10)
qdist("unif", .5)
xqgamma(.5, shape = 3, scale = 4)
xqgamma(.5, shape = 3, scale = 4, color = "black")
xqbeta(.5, shape1 = .9, shape2 = 1.4, dlwd = 1)
xqchisq(c(.25,.5,.75), df = 3)
xcbinom(c(0.80, 0.90), size = 1000, prob = 0.40)
# displayed as if continuous
xcbinom(c(0.80, 0.90), size = 5000, prob = 0.40)
xpbinom(c(480, 500, 520), size = 1000, prob = 0.48)
xpbinom(c(40, 60), size = 100, prob = 0.5)
xqpois(c(0.25, 0.5, 0.75), lambda = 12)
xcpois(0.50, lambda = 12)
xcpois(0.50, lambda = 12, refinements = list(scale_color_brewer(type = "qual", palette = 5)))

mosaic documentation built on Nov. 10, 2023, 1:11 a.m.