Aster models for life history analysis
By Charles J. Geyer, S. Wagenius, R. Shaw. 2007
168 citations recorded by the source corpus.
We present a new class of statistical models, designed for life history analysis of plants and animals, that allow joint analysis of data on survival and reproduction over multiple years, allow for variables having different probability distributions, and correctly account for the dependence of variables on earlier variables. We illustrate their utility with an analysis of data taken from an experimental study of Echinacea angustifolia sampled from remnant prairie populations in western Minnesota. These models generalize both generalized linear models and survival analysis. The joint distribution is factorized as a product of conditional distributions, each an exponential family with the conditioning variable being the sample size of the conditional distribution. The model may be heterogeneous, each conditional distribution being from a different exponential family. We show that the joint distribution is from a flat exponential family and derive its canonical parameters, Fisher information and other properties. These models are implemented in an R package 'aster' available from the Comprehensive R Archive Network, CRAN. Copyright 2007, Oxford University Press.
Subfields: Genetics, Plant Science
View Paper: https://www.semanticscholar.org/paper/62dac63e8777a57a3987fd51f5c32a783877486e
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In Genetics
In Plant Science
Citations in the corpus
- A Widespread Chromosomal Inversion Polymorphism Contributes to a Major Life-History Transition, Local Adaptation, and Reproductive Isolation (2010, methodology): “To test for effects of genetic background and the inversion on survival over the course of the season, survival analysis was conducted using ASTER, where survivorship for each field census was modeled as Bernoulli.”