Asymptotically Optimum Estimation of a Probability in Inverse Binomial Sampling under General Loss Functions
Data(s) |
06/04/2012
|
---|---|
Resumo |
The optimum quality that can be asymptotically achieved in the estimation of a probability p using inverse binomial sampling is addressed. A general definition of quality is used in terms of the risk associated with a loss function that satisfies certain assumptions. It is shown that the limit superior of the risk for p asymptotically small has a minimum over all (possibly randomized) estimators. This minimum is achieved by certain non-randomized estimators. The model includes commonly used quality criteria as particular cases. Applications to the non-asymptotic regime are discussed considering specific loss functions, for which minimax estimators are derived. |
Formato |
application/pdf |
Identificador | |
Idioma(s) |
eng |
Publicador |
E.T.S.I. Telecomunicación (UPM) |
Relação |
http://oa.upm.es/10749/1/asympt-opt16completo.pdf http://dx.doi.org/10.1016/j.jspi.2012.03.026 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jspi.2012.03.026 |
Direitos |
http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess |
Fonte |
Journal of Statistical Planning and Inference, ISSN 0378-3758, 2012-04-06 |
Palavras-Chave | #Telecomunicaciones #Matemáticas |
Tipo |
info:eu-repo/semantics/article Artículo NonPeerReviewed |