Uses Newton-Raphson to estimate the parameters of the Gamma distribution.
mlgamma(x, na.rm = FALSE, ...)mlgamma returns an object of class
univariateML.
This is a named numeric vector with maximum likelihood estimates for
shape and rate and the following attributes:
modelThe name of the model.
densityThe density associated with the estimates.
logLikThe loglikelihood at the maximum.
supportThe support of the density.
nThe number of observations.
callThe call as captured my match.call
a (non-empty) numeric vector of data values.
logical. Should missing values be removed?
rel.tol is the relative accuracy requested, defaults
to .Machine$double.eps^0.25. iterlim is a positive integer
specifying the maximum number of iterations to be performed before the
program is terminated (defaults to 100).
For the density function of the Gamma distribution see GammaDist.
Choi, S. C, and R. Wette. "Maximum likelihood estimation of the parameters of the gamma distribution and their bias." Technometrics 11.4 (1969): 683-690.
Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 17. Wiley, New York.
GammaDist for the Gamma density.