dtstudentSD: Discrete Truncated Student-t Distribution, Standard Deviation...

In mjskay/dtstudent: Discrete Truncated Student-t Distribution

Description

Discrete truncated Student-t distribution parameterized by standard deviation.

Usage

ddtstudentSD(x, nuprime, mu, sigma, width = 1, lower = 0, upper = 100,
  log = FALSE)

pdtstudentSD(q, nuprime, mu, sigma, width = 1, lower = 0, upper = 100,
  log.p = FALSE, lower.tail = TRUE)

qdtstudentSD(p, nuprime, mu, sigma, width = 1, lower = 0, upper = 100,
  log.p = FALSE, lower.tail = TRUE)

rdtstudentSD(n, nuprime, mu, sigma, width = 1, lower = 0, upper = 100)

Arguments

x, q	vector of quantiles.
nuprime	degrees of freedom - 2 of underlying Student-t distribution. nuprime > 0, and as nuprime goes to Inf, the underlying distribution becomes Normal.
mu	mode / mean of underlying Student-t distribution.
sigma	standard deviation 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.