Semiparametrically Efficient Estimation of Euclidean Parameters under\n Equality Constraints

2016/06/24 by Chris A. J. Klaassen, Klaassen, Chris A. J., Nanang Susyanto +1 · 2 citations
Mathematics · Engineering · #Statistical Methods and Inference #Advanced Statistical Methods and Models #Control Systems and Identification

paper · pdf · doi:10.48550/arxiv.1606.07749

Abstract

Assume a (semi)parametrically efficient estimator is given of the Euclidean\nparameter in a (semi)parametric model. A submodel is obtained by constraining\nthis model in that a continuously differentiable function of the Euclidean\nparameter vanishes. We present an explicit method to construct\n(semi)parametrically efficient estimators of the Euclidean parameter in such\nequality constrained submodels and prove their efficiency. Our construction is\nbased solely on the original efficient estimator and the constraining function.\n Only the parametric case of this estimation problem and a nonparametric\nversion of it have been considered in literature.\n

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• Asymptotic Inference for Constrained Regression
• Divergence and Model Adequacy, A Semiparametric Case Study

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