Aster models (Geyer, Wagenius, and Shaw, 2007, <doi:10.1093/biomet/asm030>; Shaw, Geyer, Wagenius, Hangelbroek, and Etterson, 2008, <doi:10.1086/588063>; Geyer, Ridley, Latta, Etterson, and Shaw, 2013, <doi:10.1214/13-AOAS653>) are exponential family regression models for life history analysis. They are like generalized linear models except that elements of the response vector can have different families (e. g., some Bernoulli, some Poisson, some zero-truncated Poisson, some normal) and can be dependent, the dependence indicated by a graphical structure. Discrete time survival analysis, life table analysis, zero-inflated Poisson regression, and generalized linear models that are exponential family (e. g., logistic regression and Poisson regression with log link) are special cases. Main use is for data in which there is survival over discrete time periods and there is additional data about what happens conditional on survival (e. g., number of offspring). Uses the exponential family canonical parameterization (aster transform of usual parameterization). There are also random effects versions of these models.
|Author||Charles J. Geyer <firstname.lastname@example.org>|
|Maintainer||Charles J. Geyer <email@example.com>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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