Spring Seminar Series - March 30, 2006
University of Minnesota
School of Statistics
College of Liberal Arts
Aster Models for Life History Analysis
Charles J. Geyer
School of Statistics
University of Minnesota
Thursday, March 30, 2006
3:30 PM, 115
Ford Hall
Minneapolis, East Bank Campus
Social at 3:00 PM, 300 Ford Hall
Abstract
We
present a new class of statistical models designed for life history
analysis of plants and animals. They allow joint analysis of data on
survival and reproduction over multiple years, allow for variables
having different statistical 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.
Statistically, aster models are graphical models with some resemblance
to generalized linear models and survival analysis. They have forest
graphs and the conditional distribution of each node given the parent
is a one-parameter exponential family with the parent variable the
sample size. The model may be heterogeneous, each node having a
different exponential family. We show that the joint distribution is 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
CRAN. The tech report is available at
http://www.stat.umn.edu/geyer/aster/.
Joint work with Stuart Wagenius and Ruth G. Shaw