cnorm: Central Probability in a Normal or T Distribution

Description Usage Arguments See Also Examples

View source: R/xpnorm.R

Description

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

Usage

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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, probabilities p are given as log(p).

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

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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)

ProjectMOSAIC/mosaic documentation built on Aug. 19, 2018, 9:14 a.m.