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Editor: Universidad Carlos III de Madrid. Departamento de Estadística

Issued date: 2011-11

Serie-No.: UC3M Working papers. Statistics and Econometrics11-27

Keywords: Chi-bar-square statistic , Chi-square statistic , Divergence based test-statistics , Equality constraints , Exponential family of distributions , Inequality constraints

Rights: Atribución-NoComercial-SinDerivadas 3.0 España

Abstract:Nested parameter spaces, either in the null or alternative hypothesis, constitute aguarantee for improving the performance of the tests, however in the existing literatureon order restricted inference they have been usually skipped for being studied in detNested parameter spaces, either in the null or alternative hypothesis, constitute aguarantee for improving the performance of the tests, however in the existing literatureon order restricted inference they have been usually skipped for being studied in detail.Divergence based divergence measures provide a flexible tool for creating meaningfultest-statistics, which usually contain the likelihood ratio-test statistics as special case.The existing literature on hypothesis testing with inequality constraints using phidivergencemeasures, is centered in a very specific models with multinomial sampling.The contribution of this paper consists in extending and unifying widely the existingwork: new families of test-statistics are presented, valid for nested parameter spacescontaining either equality or inequality constraints and general distributions for eithersingle or multiple populations are considered.+-





Autor: Martín, Nirian; Balakrishnan, Narayanaswami

Fuente: http://e-archivo.uc3m.es

Introducción

Universidad Carlos III de Madrid Repositorio institucional e-Archivo http:--e-archivo.uc3m.es Departamento de Estadística DES - Working Papers.
Statistics and Econometrics.
WS 2011-11 Hypothesis testing in a generic nesting framework with general population distributions Martín, Nirian http:--hdl.handle.net-10016-12618 Descargado de e-Archivo, repositorio institucional de la Universidad Carlos III de Madrid Working Paper 11-35 Statistics and Econometrics Series 27 November 2011 Departamento de Estadística Universidad Carlos III de Madrid Calle Madrid, 126 28903 Getafe (Spain) Fax (34) 91 624-98-49 HYPOTHESIS TESTING IN A GENERIC NESTING FRAMEWORK WITH GENERAL POPULATION DISTRIBUTIONS Nirian Martín1, Narayanaswami Balakrishnan2 Abstract Nested parameter spaces, either in the null or alternative hypothesis, constitute a guarantee for improving the performance of the tests, however in the existing literature on order restricted inference they have been usually skipped for being studied in detail. Divergence based divergence measures provide a flexible tool for creating meaningful test-statistics, which usually contain the likelihood ratio-test statistics as special case. The existing literature on hypothesis testing with inequality constraints using phidivergence measures, is centered in a very specific models with multinomial sampling. The contribution of this paper consists in extending and unifying widely the existing work: new families of test-statistics are presented, valid for nested parameter spaces containing either equality or inequality constraints and general distributions for either single or multiple populations are considered. Keywords: Chi-bar-square statistic, Chi-square statistic, Divergence based teststatistics, Equality constraints, Exponential family of distributions, Inequality constraints. 1 Nirian Martín, Department of Statistics, Universidad Carlos III de Madrid, Spain; Narawashami Balakrishnan, Department of Mathematics, McMaste...

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