LogGammaDist: The Extended Log Gamma Distribution

In robustloggamma: Robust Estimation of the Generalized log Gamma Model

Description

Density, distribution function, quantile function and random generation for the Extended Log Gamma distribution with parameters mu (location), sigma (scale) and lambda (shape).

Usage

dloggamma(x, mu=0, sigma=1, lambda, log=FALSE, zero=0.0001)
ploggamma(q, mu=0, sigma=1, lambda, lower.tail=TRUE,
             log.p=FALSE, zero=0.0001)
qloggamma(p, mu=0, sigma=1, lambda, zero=0.0001)
rloggamma(n, mu=0, sigma=1, lambda, zero=0.0001)

Arguments

x,q	numeric. Vector of quantiles.
p	numeric. Vector of probabilities.
n	numeric. Number of observations.
mu	numeric. Location parameter.
sigma	numeric. Scale parameter.
lambda	numeric. Shape parameter.
log, log.p	logical. If TRUE, probabilities/densities p are returned as log(p)
lower.tail	logical. If TRUE (default), probabilities are P[X <= x], otherwise, P[X > x].
zero	numeric. A threshold, values of lambda smaller than zero will report the asymptotic value of the function at 0.

Value

dloggamma gives the density, ploggamma gives the distribution function, qloggamma gives the quantile function, and rloggamma generates random deviates.

See Also

GammaDist

Examples

  set.seed(1234)
  x <- rloggamma(10, lambda=1)
  x

Example output

 [1] -4.53493970 -0.29169135 -0.24038133 -2.14664828 -0.08136333 -1.73625486
 [7]  0.36265658 -1.85329643 -1.51639382  1.26060999

robustloggamma documentation built on May 1, 2019, 9:20 p.m.