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	Provedor de dados AgEcon (1) Autor Grendar, Marian (1) Judge, George G. (1) Palavra-chave Mathematical analysis (1) Mathematical statistic (1) Research Methods/ Statistical Methods (1) Statistical theory (1) Statistics (1) Tipo do documento Working or Discussion Paper (1) Ano 2009 (1) País United States (1) Idioma Inglês (1)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 1 Primeira ... 1 ... Última Maximum Empirical Likelihood: Empty Set Problem AgEcon Grendar, Marian; Judge, George G.. In the Empirical Estimating Equations (E^3) approach to estimation and inference estimating equations are replaced by their data-dependent empirical counterparts. It is odd but with E^3 there are models where the E^3-based estimator does not exist for some data set, and does exist for others. This depends on whether or not a set of data-supported probability mass functions that satisfy the empirical estimating equations is empty for the data set. In a finite sample context, this unnoted feature invalidates methods of estimation and inference, such as the Maximum Empirical Likelihood, that operate within E^3. The empty set problem of E^3 is illustrated by several examples and possible remedies are discussed. Tipo: Working or Discussion Paper Palavras-chave: Statistical theory; Statistics; Mathematical analysis; Mathematical statistic; Research Methods/ Statistical Methods. Ano: 2009 URL: http://purl.umn.edu/53402 Registros recuperados: 1 Primeira ... 1 ... Última

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