mllomax {univariateML} | R Documentation |
Lomax distribution maximum likelihood estimation
Description
Uses Newton-Raphson to estimate the parameters of the Lomax distribution.
Usage
mllomax(x, na.rm = FALSE, ...)
Arguments
x |
a (non-empty) numeric vector of data values. |
na.rm |
logical. Should missing values be removed? |
... |
|
Details
For the density function of the Lomax distribution see Lomax.
The likelihood estimator of the Lomax distribution is unbounded when mean(x^2) < 2*mean(x)^2
. When this
happens, the likelihood converges to an exponential distribution with parameter
equal to the mean of the data. This is the natural limiting case for the Lomax
distribution, and it is reasonable to use mlexp
in this case.
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 |
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
See Also
Lomax for the Lomax density.
Examples
set.seed(3)
mllomax(extraDistr::rlomax(100, 2, 4))
# The maximum likelihood estimator may fail if the data is exponential.
## Not run:
set.seed(5)
mllomax(rexp(10))
## End(Not run)