Fence methods for mixed model selection

Details Fence methods for mixed model selection Fence methods for mixed model selection

2008-08-07

arxiv.org/abs/0808.0985v1

Annals of Statistics 2008, Vol. 36, No. 4, 1669-1692

Mathematics

Statistics Theory

Published in at http://dx.doi.org/10.1214/07-AOS517 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of

Scientific paper

10.1214/07-AOS517

Many model search strategies involve trading off model fit with model complexity in a penalized goodness of fit measure. Asymptotic properties for these types of procedures in settings like linear regression and ARMA time series have been studied, but these do not naturally extend to nonstandard situations such as mixed effects models, where simple definition of the sample size is not meaningful. This paper introduces a new class of strategies, known as fence methods, for mixed model selection, which includes linear and generalized linear mixed models. The idea involves a procedure to isolate a subgroup of what are known as correct models (of which the optimal model is a member). This is accomplished by constructing a statistical fence, or barrier, to carefully eliminate incorrect models. Once the fence is constructed, the optimal model is selected from among those within the fence according to a criterion which can be made flexible. In addition, we propose two variations of the fence. The first is a stepwise procedure to handle situations of many predictors; the second is an adaptive approach for choosing a tuning constant. We give sufficient conditions for consistency of fence and its variations, a desirable property for a good model selection procedure. The methods are illustrated through simulation studies and real data analysis.

Affiliated with

Also associated with

No associations

Rating

Fence methods for mixed model selection does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Fence methods for mixed model selection, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Fence methods for mixed model selection will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-213410