Data/hora: 08/06/2024 09:25:12

Provedor de dados: | 31
País: | United States
Título: | Maximum Empirical Likelihood: Empty Set Problem
Autores: | Grendar,   Marian; Judge,   George G.
Data: | 2009-09-10
Ano: | 2009
Palavras-chave: | Statistical theory; Statistics; Mathematical analysis; Mathematical statistic; Research Methods/ Statistical Methods.
Resumo: | 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
Idioma: | Inglês
Identificador: | http://purl.umn.edu/53402

Relação:

University of California, Berkeley&gt;Department of Agricultural and Resource Economics&gt;CUDARE Working Papers

CUDARE Working Papers

1090

Formato: | 10