dcom: The COM-Poisson Distribution

In compoisson: Conway-Maxwell-Poisson Distribution

Description

Probability mass function and random generation for the COM-Poisson distribution for given values of the parameters.

Usage

	dcom(x, lambda, nu, z = NULL)
	rcom(n, lambda, nu, log.z = NULL)

Arguments

x	level to evaluate the PMF at
lambda	value of lambda parameter
nu	value of nu parameter
z	normalizing constant, computed if not specified
n	number of random values to return
log.z	natural log of z

Details

Computes the probability mass function of the COM-Poisson distribution

f(x) = (1/Z) (lambda^x)/(x!^nu).

Value

dcom gives the probability that a random COM-Poisson variable X takes value x. rcom gives a vector of n random values sampled from the COM-Poisson distribution.

Author(s)

Jeffrey Dunn

References

Shmueli, G., Minka, T. P., Kadane, J. B., Borle, S. and Boatwright, P., “A useful distribution for fitting discrete data: Revival of the Conway-Maxwell-Poisson distribution,” J. Royal Statist. Soc., v54, pp. 127-142, 2005.

See Also

com.loglikelihood, com.log.density

Examples

	data(insurance);
	fit = com.fit(Lemaire);
	dcom(0, fit$lambda, fit$nu, fit$z);
	r = rcom(10, fit$lambda, fit$nu);

Example output

Loading required package: MASS
[1] 0.9066425

compoisson documentation built on May 1, 2019, 11:17 p.m.