Point and interval estimation for the logistic distribution based on record data
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Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/112738
Tipus de documentArticle
Data publicació2016-06-17
EditorInstitut d'Estadística de Catalunya
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
In this paper, based on record data from the two-parameter logistic distribution, the maximum likelihood and Bayes estimators for the two unknown parameters are derived. The maximum likelihood estimators and Bayes estimators can not be obtained in explicit forms. We present a simplemethod of deriving explicit maximum likelihood estimators by approximating the likelihood function. Also, an approximation based on the Gibbs sampling procedure is used to obtain the Bayes estimators. Asymptotic confidence intervals, bootstrap confidence intervals and credible intervals are also proposed. Monte Carlo simulations are performed to compare the performances of the different proposed methods. Finally, one real data set has been analysed for illustrative purposes.
CitacióAsgharzadeh, A.; Valiollahi, R.; Abdi, M. Point and interval estimation for the logistic distribution based on record data. "SORT", 17 Juny 2016, vol. 1, p. 89-112.
ISSN1696-2281
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40.1.4.asgharzadeh-etal.pdf | 1,152Mb | Visualitza/Obre |