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This work is an extension of the state space model for Poisson count data, Poisson-Gamma model, towards a semiparametric specification. Just like the generalized additive models (GAM), cubic splines are used for covariate smoothing. The semiparametric models are fitted by an iterative process that combines maximization of likelihood and backfitting algorithm.
| Version: | 0.4.17 |
| Depends: | R (≥ 3.0.0), stats, utils |
| Published: | 2022-08-19 |
| DOI: | 10.32614/CRAN.package.pgam |
| Author: | Washington Junger |
| Maintainer: | Washington Junger <wjunger at ims.uerj.br> |
| License: | GPL-3 | file LICENSE |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | pgam results |
| Reference manual: | pgam.pdf |
| Package source: | pgam_0.4.17.tar.gz |
| Windows binaries: | r-devel: pgam_0.4.17.zip, r-release: pgam_0.4.17.zip, r-oldrel: pgam_0.4.17.zip |
| macOS binaries: | r-release (arm64): pgam_0.4.17.tgz, r-oldrel (arm64): pgam_0.4.17.tgz, r-release (x86_64): pgam_0.4.17.tgz, r-oldrel (x86_64): pgam_0.4.17.tgz |
| Old sources: | pgam archive |
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