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2006•Unpublished venueRequires access

Testing Estimator's Credibility¿Part II: Other Tests

Xiaoning Li, Zhanlue Zhao

Open publisher page 7 citations

Abstract

For pt.I see ibid., p.Z001330-7 (2006). Many estimators and filters provide assessments of their own estimation error. Are these self-assessments trustable? What is the degree to which they are trustable? This is Part II of a two-part series that provides answers to some of these questions, referred to as the credibility of the estimators. It proposes several tests for credibility and a test-based solution to the problem of comparing estimators' credibility. Numerical examples are provided to illustrate the utility and effectiveness of the proposed tests

About this research paper

What this paper is about

For pt.I see ibid., p.Z001330-7 (2006). Many estimators and filters provide assessments of their own estimation error. Are these self-assessments trustable? What is the degree to which they are trustable? This is Part II of a two-part series that provides answers to some of these questions, referred to as the credibility of the estimators. It proposes several tests for credibility and a test-based solution to the problem of comparing estimators' credibility. Numerical examples are provided to illustrate the utility and effectiveness of the proposed tests

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

For pt.I see ibid., p.Z001330-7 (2006). Many estimators and filters provide assessments of their own estimation error. Are these self-assessments trustable? What is the degree to which they are trustable? This is Part II of a two-part series that provides answers to some of these questions, referred to as the credibility of the estimators. It proposes several tests for credibility and a test-based solution to the problem of comparing estimators' credibility. Numerical examples are provided to illustrate the utility and effectiveness of the proposed tests

Key concepts: Credibility, Estimator, Computer science, Test (biology), Series (stratigraphy), Degree (music), Econometrics, Mathematics

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