Description Usage Arguments Details Value Author(s) References See Also Examples
Computes the maximum likelihood estimates of the COM-Poisson model for given count data.
1 | com.fit(x)
|
x |
matrix of count data |
The argument x should consist of a matrix where the first column is the level and the second column is the count for the corresponding level.
Returns an object containing four fields:
lambda |
Estimate of the lambda parameter |
nu |
Estimate of the nu parameter |
z |
Normalizing constant |
fitted.values |
Estimated counts at given levels |
Jeffrey Dunn
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.
com.compute.z
, com.loglikelihood
1 2 |
Loading required package: MASS
$lambda
[1] 0.09497434
$nu
[1] 0.2720292
$z
[1] 1.102971
$fitted.values
[1] 96987.174132 9211.293330 724.499276 51.033262 3.324158
$log.likelihood
[,1]
[1,] -36101.1
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.