A Selection Problem in Measurement Error Models

Abstract

This paper deals with a selection problem for linear measurement error models. A selection procedure is constructed, and its corresponding asymptotic optimality is also investigated. It is shown that with the assumption of the existence of the a(-th) (a>2) moment, the expected risk of the proposed selection procedure converges to 0 with the rate of order o(n(-(a/2-1))). It is further shown that when the moment generating functions of the corresponding variables exist, the expected risk of the proposed selection procedure converges with exponential order O(e(-c*n)) under mild conditions, where c* is a positive constant.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1997
Accession Number
ADA332193

Entities

People

  • Shanti Gupta
  • Xun Lin

Organizations

  • Purdue University

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  • Abstracts
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  • Estimators
  • Experimental Design
  • Measurement
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  • Mathematics

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  • Approximation Theory.
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