Package: aster
Version: 1.1-2
Date: 2021-06-11
Title: Aster Models
Author: Charles J. Geyer <charlie@stat.umn.edu>
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>
Depends: R (>= 3.6.0)
Imports: stats, trust
Suggests: numDeriv
ByteCompile: TRUE
Description: 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.
License: MIT + file LICENSE
URL: http://www.stat.umn.edu/geyer/aster/
NeedsCompilation: yes
Packaged: 2021-06-12 03:10:35 UTC; geyer
Repository: CRAN
Date/Publication: 2021-06-13 04:40:32 UTC

Description: Aster models are exponential family graphical models that
combine aspects of generalized linear models and survival

Package: aster2
Version: 0.2-1
Date: 2015-05-11
Title: Aster Models
Author: Charles J. Geyer <charlie@stat.umn.edu>.
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>
Depends: R (>= 2.10.0)
Suggests: aster
ByteCompile: TRUE
Description: Aster models 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, 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).
Unlike the aster package, this package does dependence groups (nodes of
the graph need not be conditionally independent given their predecessor
node), including multinomial and two-parameter normal as families.  Thus
this package also generalizes mark-capture-recapture analysis.
License: GPL (>= 2)
URL: http://www.stat.umn.edu/geyer/aster/
NeedsCompilation: yes
Packaged: 2015-05-11 16:51:40 UTC; geyer
Repository: CRAN
Date/Publication: 2015-05-11 20:36:37