cold: Count Longitudinal Data

Performs regression analysis for longitudinal count data, allowing for serial dependence among observations from a given individual and two dimensional random effects on the linear predictor. Estimation is via maximization of the exact likelihood of a suitably defined model. Missing values and unbalanced data are allowed. Details can be found in the accompanying scientific papers: Goncalves & Cabral (2021, Journal of Statistical Software, <doi:10.18637/jss.v099.i03>) and Goncalves et al. (2007, Computational Statistics & Data Analysis, <doi:10.1016/j.csda.2007.03.002>).

Version: 2.0-3
Depends: R (≥ 3.5.3), methods, stats, graphics, grDevices, utils, cubature, MASS
Published: 2021-08-25
Author: M. Helena Goncalves and M. Salome Cabral, apart from a set of Fortran-77 subroutines written by R. Piessens and E. de Doncker, belonging to the suite "Quadpack".
Maintainer: M. Helena Goncalves <mhgoncal at ualg.pt>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: cold citation info
Materials: NEWS
CRAN checks: cold results

Documentation:

Reference manual: cold.pdf

Downloads:

Package source: cold_2.0-3.tar.gz
Windows binaries: r-devel: cold_2.0-3.zip, r-devel-UCRT: cold_2.0-3.zip, r-release: cold_2.0-3.zip, r-oldrel: cold_2.0-3.zip
macOS binaries: r-release (arm64): cold_2.0-3.tgz, r-release (x86_64): cold_2.0-3.tgz, r-oldrel: cold_2.0-3.tgz
Old sources: cold archive

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