| HalfT | R Documentation |
Density, distribution function, quantile function and random generation for the half-t distribution.
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)
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 |
vector of probabilities. |
n |
number of observations. If |
If X follows t distribution parametrized by degrees of freedom \nu
and scale \sigma, then |X| follows half-t distribution parametrized
by degrees of freedom \nu and scale \sigma.
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.
HalfNormal, HalfCauchy
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)
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