dtstudent: Discrete Truncated Student-t Distribution, Scale...

In mjskay/dtstudent: Discrete Truncated Student-t Distribution

Description

Discrete truncated Student-t distribution.

Usage

ddtstudent(x, nu, mu, scale, width = 1, lower = 0, upper = 100,
  log = FALSE)

pdtstudent(q, nu, mu, scale, width = 1, lower = 0, upper = 100,
  log.p = FALSE, lower.tail = TRUE)

qdtstudent(p, nu, mu, scale, width = 1, lower = 0, upper = 100,
  log.p = FALSE, lower.tail = TRUE)

rdtstudent(n, nu, mu, scale, width = 1, lower = 0, upper = 100)

Arguments

x, q	vector of quantiles.
nu	Degrees of freedom parameter of underlying Student-t distribution. nu > 0, and as nu goes to Inf, the underlying distribution becomes Normal.
mu	mode / mean of underlying Student-t distribution.
scale	scale of underlying Student-t distribution.
width	width of the intervals used for discretization.
lower	lower truncation point.
upper	upper truncation point.
log, log.p	logical; if TRUE, probabilities p are given as log(p).
lower.tail	logical; if TRUE (default), probabilities are P[X ≤ x] otherwise, P[X > x].
p	vector of probabilities.
n	number of observations.

Author(s)

Matthew Kay

mjskay/dtstudent documentation built on May 23, 2019, 1:04 a.m.