comp_mu_loglik: Calculate the Log-Likelihood of the COM-Poisson model

In mpcmp: Mean-Parametrized Conway-Maxwell Poisson (COM-Poisson) Regression

Description

A function to compute the log-likelihood of the COM-Poisson model.

Usage

comp_mu_loglik(param, y, xx, offset, summax)

comp_mu_neg_loglik_log_nu_only(log_nu, mu, y, summax)

Arguments

param	numeric vector: the model coefficients & the current value of nu. It is assumed that nu is in the last position of param.
y	numeric vector: response variable
xx	numeric matrix: the explanatory variables
offset	numeric vector: a vector of length equal to the number of cases
summax	maximum number of terms to be considered in the truncated sum
log_nu	numeric: nu in log-scale
mu	numeric vector: fitted mean parameters

Value

comp_mu_loglik returns the log-likelihood value of the COM-Poisson model based on Huang (2018). comp_mu_neg_loglik_log_nu_only returns the negative log-likelihood value of the COM-Poisson model based on Ribeiro Jr et al. (2018)'s specification to use in conjunction with optim.

mpcmp documentation built on Oct. 26, 2020, 9:07 a.m.