poislindll: Maximum Likelihood Estimation for the Discrete...

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Maximum Likelihood Estimation for the Discrete Poisson-Lindley Distribution

Description

Performs maximum likelihood estimation for the parameter of the Poisson-Lindley distribution.

Usage

poislind.ll(x, theta = NULL, ...) 

Arguments

x	A vector of raw data which is distributed according to a Poisson-Lindley distribution.
theta	Optional starting value for the parameter. If NULL, then the method of moments estimator is used.
...	Additional arguments passed to the mle function.

Details

The discrete Poisson-Lindley distribution is a compound distribution that, potentially, provides a better fit for count data relative to the traditional Poisson and negative binomial distributions.

Value

See the help file for mle to see how the output is structured.

References

Ghitany, M. E. and Al-Mutairi, D. K. (2009), Estimation Methods for the Discrete Poisson-Lindley Distribution, Journal of Statistical Computation and Simulation, 79, 1–9.

Sankaran, M. (1970), The Discrete Poisson-Lindley Distribution, Biometrics, 26, 145–149.

See Also

mle, PoissonLindley

Examples

## Maximum likelihood estimation for randomly generated data
## from the Poisson-Lindley distribution. 

set.seed(100)

pl.data <- rpoislind(n = 500, theta = 0.5)
out.pl <- poislind.ll(pl.data)
stats4::coef(out.pl)
stats4::vcov(out.pl)

tolerance documentation built on May 29, 2024, 7:38 a.m.