logical; if TRUE, probabilities p are given as log(p).
lower.tail
logical; if TRUE (default), probabilities are \(P[X \le x]\)
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 normal distribution centered at 0 and parametrized
by scale \(\sigma\), then \(|X|\) follows half-normal distribution
parametrized by scale \(\sigma\). Half-t distribution with \(\nu=\infty\)
degrees of freedom converges to half-normal distribution.
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.