Moderate Deviations Of Generalized Method Of Moments And Empirical Likelihood Estimators

This paper studies moderate deviation behaviors of the generalized method of moments and generalized empirical likelihood estimators for generalized estimating equations, where the number of equations can be larger than the number of unknown parameters. The authors consider two cases for the data generating probability measure: the model assumption and local contaminations or deviations from the model assumption. For both cases, they characterize the first-order terms of the moderate deviation error probabilities of these estimators.

Provided by: Yale University Topic: Big Data Date Added: Feb 2011 Format: PDF

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