GIB-UFSCar/USP

Seminário do Grupo de Inferência Bayesiana (GIB-UFSCar/USP)

03/04/2009-14 horas ( horário)

Sala de seminários do Departamento de Estatística- UFSCar-São Carlos-SP

Títuo: Exploring Large Regression Model Spaces via Trans-dimensional Genetic Algorithms

Ricardo Ehlers (ICMC-USP)

Abstract

We develop for regression models trans-dimensional genetic algorithms
for the exploration of large model spaces. Our algorithms can be used
in two different ways. The first possibility is to search the best
model according to some criteria such as AIC or BIC. The second
possibility is to use our algorithms to explore the model space,
search for the most probable models and estimate their posterior
probabilities. This is accomplished by the use of genetic operators
embedded in a reversible jump Markov chain
Monte Carlo algorithm in the model space with several chains.
As these chains run simultaneously and learn from each other via the
genetic operators, our algorithm efficiently explores the large model
space and easily escapes local maxima regions common in the presence of
highly correlated regressors. We illustrate the power of our
trans-dimensional genetic algorithms with applications to two real
data sets.

Key Words: Model comparison, Genetic algorithms, Markov chain
Monte Carlo, reversible jump MCMC.

Estão todos convidados para este seminário especial às 14:00 h. Lembramos que neste semestre o GIB realizará mensalmente um seminário conjunto com o ICMC-USP. Abraços, Josemar