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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