PowerExponentialPower: The Power Exponential Power Distribution

In anyosa/powdist: Power and Reversal Power Distributions

Description

Density, distribution function, quantile function and random generation for the power exponential power distribution with parameters mu, sigma, lambda and k.

Usage

dpexpow(x, lambda = 1, mu = 0, sigma = 1, k = 0, log = FALSE)

ppexpow(q, lambda = 1, mu = 0, sigma = 1, k = 0, lower.tail = TRUE,
  log.p = FALSE)

qpexpow(p, lambda = 1, mu = 0, sigma = 1, k = 0, lower.tail = TRUE,
  log.p = FALSE)

rpexpow(n, lambda = 1, mu = 0, sigma = 1, k = 0)

Arguments

x, q	vector of quantiles.
mu, sigma	location and scale parameters.
k, lambda	shape 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.

Details

The power exponential power distribution has density

f(x)=[λ/σ][exp(-(x-μ)/σ)/(1+exp(-(x-μ)/σ)))^2][exp((x-μ)/σ)/(1+exp((x-μ)/σ)]^(λ-1),

where -∞<μ<∞ is the location paramether, σ^2>0 the scale parameter and λ>0 and k the shape parameters.

References

Lemonte A. and Bazán J.L.

Examples

dpexpow(1, 1, 3, 4, 1)
ppexpow(1, 1, 3, 4, 1)
qpexpow(0.2, 1, 3, 4, 1)
rpexpow(5, 2, 3, 4, 1)

anyosa/powdist documentation built on May 22, 2019, 4:39 p.m.