lss: Measures of location, scale and shape measures for a...

In sglg: Fitting Semi-Parametric Generalized log-Gamma Regression Models

Measures of location, scale and shape measures for a generalized log-gamma distribution

Description

lss is used to obtain the mean, median, mode, variance, coefficient of variation, skewness and kurtosis for a generalized log-gamma distribution.

Usage

lss(mu = 0, sigma = 1, lambda = 1)

Arguments

mu	numeric, represents the location parameter of a generalized log-gamma distribution. Default value is 0.
sigma	numeric, represents the scale parameter of a generalized log-gamma distribution. Default value is 1.
lambda	numeric, represents the shape parameter of a generalized log-gamma distribution. Default value is 1.

Author(s)

Carlos Alberto Cardozo Delgado <[e-mail]>

References

Carlos Alberto Cardozo Delgado, Semi-parametric generalized log-gamma regression models. Ph. D. thesis. Sao Paulo University.

National Institute of Standards and Technology, NIST. Engineering Statistics Handbook. https://www.itl.nist.gov/div898/handbook/eda/section3/eda366g.htm

Examples

lss(0,1,-1)    # Extreme value type I distribution, maximum case.
lss(0,1,1)     # Extreme value type I distribution, minimum case.
lss(0,1,0.01) # Standard normal distribution.

sglg documentation built on Sept. 4, 2022, 9:05 a.m.