Imputation Estimators Partially Correct for Model Misspecification

Details Imputation Estimators Partially Correct for Model Misspecification Imputation Estimators Partially Correct for Model Misspecification

2009-11-04

arxiv.org/abs/0911.0930v2

Statistics

Methodology

major rewrite, beta-binomial example removed, model based clustering is added to the mixture model example, Bayesian approach

Scientific paper

Inference problems with incomplete observations often aim at estimating population properties of unobserved quantities. One simple way to accomplish this estimation is to impute the unobserved quantities of interest at the individual level and then take an empirical average of the imputed values. We show that this simple imputation estimator can provide partial protection against model misspecification. We illustrate imputation estimators' robustness to model specification on three examples: mixture model-based clustering, estimation of genotype frequencies in population genetics, and estimation of Markovian evolutionary distances. In the final example, using a representative model misspecification, we demonstrate that in non-degenerate cases, the imputation estimator dominates the plug-in estimate asymptotically. We conclude by outlining a Bayesian implementation of the imputation-based estimation.

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