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 |
Documentation:
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