| gamma_fit {goft} | R Documentation |
Fitting the Gamma distribution to data
Description
Fits a Gamma distribution to a random sample of positive real numbers using Villasenor and Gonzalez-Estrada (2015) parameter estimators.
Usage
gamma_fit(x)
Arguments
x |
a numeric data vector containing a random sample of positive real numbers. |
Details
The Gamma distribution with shape and scale parameters is considered. The scale parameter is estimated by the unbiased sample estimator of the covariance of X and log(X). The shape parameter is estimated by the ratio of the sample mean of X and the scale parameter estimator.
Value
Shape and scale parameter estimates.
Author(s)
Elizabeth Gonzalez-Estrada egonzalez@colpos.mx, Jose A. Villasenor-Alva
References
Villasenor, J.A. and Gonzalez-Estrada, E. (2015). A variance ratio test of fit for Gamma distributions. Statistics and Probability Letters, 96 1, 281-286. http://dx.doi.org/10.1016/j.spl.2014.10.001
See Also
gamma_test for testing the Gamma distribution hypothesis.
Examples
# Fitting a gamma distribution to the logarithm of variable Loss contained in
# the danishuni data set
library(fitdistrplus)
data(danishuni)
logLoss <- log(danishuni$Loss) # logarithm of Loss variable
logLoss <- logLoss[logLoss > 0] # observations > 0
gamma_fit(logLoss)