mlgompertz: Gompertz distribution maximum likelihood estimation

In univariateML: Maximum Likelihood Estimation for Univariate Densities

Gompertz distribution maximum likelihood estimation

Description

Uses Newton-Raphson to estimate the parameters of the Gompertz distribution.

Usage

mlgompertz(x, na.rm = FALSE, ...)

Arguments

x	a (non-empty) numeric vector of data values.
na.rm	logical. Should missing values be removed?
...	reltol 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).

Details

For some data sets the maximum likelihood estimator of b fails to exist since the root of the profile maximum likelihood equation is non-positive. The value 1e-06 is returned in this case, along with a warning.

For the density function of the Gompertz distribution see Gompertz.

Value

mlgompertz returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for a and b and the following attributes:

model	The name of the model.
density	The density associated with the estimates.
logLik	The loglikelihood at the maximum.
support	The support of the density.
n	The number of observations.
call	The call as captured my match.call

References

Lenart, A. (2012). The Gompertz distribution and Maximum Likelihood Estimation of its parameters - a revision. MPIDR WORKING PAPER WP 2012-008. https://www.demogr.mpg.de/papers/working/wp-2012-008.pdf

See Also

Gompertz for the Gompertz density.

Examples

mlgompertz(precip)

univariateML documentation built on April 3, 2025, 11:09 p.m.