normalp (version 0.7.2)

qnormp: Quantiles of an exponential power distribution

Description

Quantiles for the exponential power distribution with location parameter mu, scale parameter sigmap and shape parameter p.

Usage

qnormp(pr, mu=0, sigmap=1, p=2, lower.tail=TRUE, log.pr=FALSE)

Value

qnormp gives the quantiles of an exponential power distribution.

Arguments

pr

Vector of probabilities.

mu

Vector of location parameters.

sigmap

Vector of scale parameters.

p

Shape parameter.

lower.tail

Logical; if TRUE (default), probabilities are \(P [X\leq x]\), otherwise, \(P[X>x]\).

log.pr

Logical; if TRUE, probabilities \(pr\) are given as \(log(pr)\).

Author

Angelo M. Mineo

Details

If mu, sigmap or p are not specified they assume the default values 0, 1 and 2, respectively. The exponential power distribution has density function

$$f(x) = \frac{1}{2 p^{(1/p)} \Gamma(1+1/p) \sigma_p} e^{-\frac{|x - \mu|^p}{p \sigma_p^p}}$$

where \(\mu\) is the location parameter, \(\sigma_p\) the scale parameter and \(p\) the shape parameter. When \(p=2\) the exponential power distribution becomes the Normal Distribution, when \(p=1\) the exponential power distribution becomes the Laplace Distribution, when \(p\rightarrow\infty\) the exponential power distribution becomes the Uniform Distribution.

See Also

Normal for the Normal distribution, Uniform for the Uniform distribution, and Special for the Gamma function.

Examples

Run this code
## Compute the quantiles for a vector of probabilities x
## with mu=1, sigmap=2 and p=1.5
x <- 0.3
q <- qnormp(x, 1, 2, 1.5)
q

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