mosaic (version 1.9.1)

cnorm: Central Probability in a Normal or T Distribution

Description

These versions of the quantile functions take a vector of central probabilities as its first argument.

Usage

cnorm(p, mean = 0, sd = 1, log.p = FALSE, side = c("both", "upper", "lower"))
ct(p, df, ncp, log.p = FALSE, side = c("upper", "lower", "both"))

Arguments

p

vector of probabilities.

mean

vector of means.

sd

vector of standard deviations.

log.p

logical. If TRUE, uses the log of probabilities.

side

One of "upper", "lower", or "both" indicating whether a vector of upper or lower quantiles or a matrix of both should be returned.

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.

See Also

stats::qnorm(), cdist()

Examples

qnorm(.975)
cnorm(.95)
xcnorm(.95)
xcnorm(.95, verbose = FALSE, return = "plot") |>
  gf_refine(
  scale_fill_manual( values = c("navy", "limegreen")),
  scale_color_manual(values = c("black", "black")))
cnorm(.95, mean = 100, sd = 10)
xcnorm(.95, mean = 100, sd = 10)