Finite population estimators in stochastic search variable selection

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Date

2012-12

Authors

Clyde, MA
Ghosh, J

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Bayesian model averaging, Horvitz-Thompson estimator, Inclusion probability, Markov chain Monte Carlo, Median probability model, Model uncertainty, Variable selection

Citation

Published Version (Please cite this version)

10.1093/biomet/ass040

Publication Info

Clyde, MA, and J Ghosh (2012). Finite population estimators in stochastic search variable selection. BIOMETRIKA, 99(4). pp. 981–988. 10.1093/biomet/ass040 Retrieved from https://hdl.handle.net/10161/11723.

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Scholars@Duke

Clyde

Merlise Clyde

Professor of Statistical Science

Model uncertainty and choice in prediction and variable selection problems for linear, generalized linear models and multivariate models. Bayesian Model Averaging. Prior distributions for model selection and model averaging. Wavelets and adaptive kernel non-parametric function estimation. Spatial statistics. Experimental design for nonlinear models. Applications in proteomics, bioinformatics, astro-statistics, air pollution and health effects, and environmental sciences.


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