2021-04-18T15:10:39Z
http://oa.upm.es/cgi/oai2
oai:oa.upm.es:10749
2016-04-20T18:59:07Z
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Asymptotically Optimum Estimation of a Probability in Inverse Binomial Sampling under General Loss Functions
Mendo Tomás, Luis
Telecommunications
Mathematics
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.
E.T.S.I. Telecomunicación (UPM)
http://creativecommons.org/licenses/by/3.0/es/
2012-04-06
info:eu-repo/semantics/article
Article
Journal of Statistical Planning and Inference, ISSN 0378-3758, 2012-04-06
NonPeerReviewed
application/pdf
eng
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jspi.2012.03.026
http://oa.upm.es/10749/