Performs regression analysis for longitudinal count data using a self-decomposable probability distribution, a random intercept term is also allowed. Estimation is via maximization of the exact likelihood of a suitably defined model. Missing values and unbalanced data are allowed.
|Author||M. Helena Gonalves and M. Salom Cabral, apart from a set of Fortran-77 subroutines written by R. Piessens and E. de Doncker, belonging to the suite "Quadpack".|
|Date of publication||2015-04-15 20:46:43|
|Maintainer||M. Helena Gonalves <firstname.lastname@example.org>|
|License||GPL (>= 2)|
anova-methods: Methods for Function anova in Package "cold"
cold: Fit of Parametric Models for Count Longitudinal Data via...
cold-class: Class "cold" for Results of a Maximum Likelihood Estimation
coldControl: Auxiliary for Controlling "cold" Fitting
coldIntegrate: Auxiliary for Controlling "cold" Fitting
cold-package: Count Longitudinal Data
fitted-methods: Extract "cold" Fitted Values
getAIC: Extract the Akaike Information Criterion
getAIC-methods: Extract the Akaike Information Criterion
getLogLik: Extract Log-Likelihood
getLogLik-methods: Extract Log-Likelihood
plot-methods: Methods for Function plot in Package "cold"
predict-methods: Extract "cold" Predict Values
resid-methods: Extract "cold" Residuals
show-methods: Methods for Function show in Package "cold"
summary.cold-class: Class "summary.cold", Summary of "cold" Objects
summary-methods: Methods for Function summary in Package "cold"