HalfT: Half-t distribution

Description Usage Arguments Details References See Also Examples

Description

Density, distribution function, quantile function and random generation for the half-t distribution.

Usage

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dht(x, nu, sigma = 1, log = FALSE)

pht(q, nu, sigma = 1, lower.tail = TRUE, log.p = FALSE)

qht(p, nu, sigma = 1, lower.tail = TRUE, log.p = FALSE)

rht(n, nu, sigma = 1)

Arguments

x, q

vector of quantiles.

nu, sigma

positive valued degrees of freedom and scale parameters.

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. If length(n) > 1, the length is taken to be the number required.

Details

If X follows t distribution parametrized by degrees of freedom ν and scale σ, then |X| follows half-t distribution parametrized by degrees of freedom ν and scale σ.

References

Gelman, A. (2006). Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper). Bayesian analysis, 1(3), 515-534.

Jacob, E. and Jayakumar, K. (2012). On Half-Cauchy Distribution and Process. International Journal of Statistika and Mathematika, 3(2), 77-81.

See Also

HalfNormal, HalfCauchy

Examples

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x <- rht(1e5, 2, 2)
hist(x, 500, freq = FALSE, xlim = c(0, 100))
curve(dht(x, 2, 2), 0, 100, col = "red", add = TRUE)
hist(pht(x, 2, 2))
plot(ecdf(x), xlim = c(0, 100))
curve(pht(x, 2, 2), 0, 100, col = "red", lwd = 2, add = TRUE)

extraDistr documentation built on June 6, 2018, 1:04 a.m.

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