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 |
| DOI: | 10.32614/CRAN.package.cold |
| 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 |
| In views: | MissingData |
| CRAN checks: | cold results |
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