Likelihood Ratio Test for nu = 1 of a COM-Poisson model

Perform a likelihood ratio chi-squared test for nu = 1 of a COM-Poisson model. The test statistics is calculated as 2*(llik- llik_0) where llik and llik_0 are the log-likelihood of a COM-Poisson and Poisson model respectively. The test statistic has 1 degrees of freedom.

Usage

LRTnu(object, digits = 3)

Arguments

object: an object class 'cmp', obtained from a call to glm.cmp
digits: numeric; minimum number of significant digits to be used for most numbers.

Value

An object of class "htest" (see t.test for the generic structure), with components:

statistic: the likelihood ratio test statistic.
parameter: the degrees of freedom for the test statistic (always 1).
p.value: the p-value for the test.
estimate: the log-likelihood of the fitted mean-CMP model and of the corresponding Poisson model.
method: a character string describing the test.
data.name: a character string giving the name of the model object.

Printing the returned object (e.g. via automatic printing at the console) displays a formatted summary of the test.

References

Huang, A. (2017). Mean-parametrized Conway-Maxwell-Poisson regression models for dispersed counts. Statistical Modelling 17, 359–380.

Examples

data(takeoverbids)
M.bids <- glm.cmp(numbids ~ leglrest + rearest + finrest + whtknght
  + bidprem + insthold + size + sizesq + regulatn, data = takeoverbids)
LRTnu(M.bids)
#> 
#> 	Likelihood ratio test for testing nu = 1
#> 
#> data:  M.bids
#> LR statistic = 9.72, df = 1, p-value = 0.001821
#> sample estimates:
#> log-lik for Mean-CMP  log-lik for Poisson 
#>                 -180                 -185 
#>