mllomax: Lomax distribution maximum likelihood estimation

Description

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

Usage

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

Value

mllomax returns an object of class

univariateML. This is a named numeric vector with maximum likelihood estimates for lambda and kappa 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

Arguments

x: a (non-empty) numeric vector of data values.
na.rm: logical. Should missing values be removed?
...: lambda0 an optional starting value for the lambda parameter. Defaults to median(x). 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).

Details

For the density function of the Lomax distribution see Lomax. The maximum likelihood estimate will frequently fail to exist. This is due to the parameterization of the function which does not take into account that the density converges to an exponential along certain values of the parameters, see vignette("Distribution Details", package = "univariateML").

References

Kleiber, Christian; Kotz, Samuel (2003), Statistical Size Distributions in Economics and Actuarial Sciences, Wiley Series in Probability and Statistics, 470, John Wiley & Sons, p. 60

Examples

Run this code

set.seed(3)
mllomax(extraDistr::rlomax(100, 2, 4))

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