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Asymptotically Optimum Estimation of a Probability in Inverse Binomial Sampling under General Loss Functions
Citation
Mendo Tomás, Luis 
ORCID: https://orcid.org/0000-0001-5691-714X
(2012).
Asymptotically Optimum Estimation of a Probability in Inverse Binomial Sampling under General Loss Functions.
"Journal of Statistical Planning and Inference"
;
ISSN 0378-3758.
https://doi.org/10.1016/j.jspi.2012.03.026.
Description
| Title: | Asymptotically Optimum Estimation of a Probability in Inverse Binomial Sampling under General Loss Functions |
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| Author/s: |
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| Item Type: | Article |
| Título de Revista/Publicación: | Journal of Statistical Planning and Inference |
| Date: | 6 April 2012 |
| ISSN: | 0378-3758 |
| Subjects: | |
| Freetext Keywords: | Sequential estimation; Asymptotic properties; Minimax estimators; Inverse binomial sampling |
| Faculty: | E.T.S.I. Telecomunicación (UPM) |
| Department: | Señales, Sistemas y Radiocomunicaciones |
| Creative Commons Licenses: | Recognition |
Abstract
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.
More information
| Item ID: | 10749 |
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| DC Identifier: | https://oa.upm.es/10749/ |
| OAI Identifier: | oai:oa.upm.es:10749 |
| DOI: | 10.1016/j.jspi.2012.03.026 |
| Deposited by: | Dr. Luis Mendo |
| Deposited on: | 08 May 2012 07:34 |
| Last Modified: | 20 Apr 2016 18:59 |
