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	Provedor de dados Anais da ABC (AABC) (2) Autor ALMEIDA,MARCO P. (1) DEY,SANKU (1) LOUZADA,FRANCISCO (1) MOALA,FERNANDO A. (1) RAMOS,PEDRO L. (1) TOMAZELLA,VERA L.D. (1) Mais... Palavra-chave Objective prior (2) Bayesian analysis (1) Bayesian prediction (1) Censored data (1) Elicitation (1) Gompertz distribution (1) Jeffreys prior (1) Maximal data information prior (1) Subjective prior (1) Wilson-Hilferty distribution. (1) Mais... Tipo do documento Info:eu-repo/semantics/article (2) Ano 2019 (1) 2018 (1) País Brazil (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Objective and subjective prior distributions for the Gompertz distribution Anais da ABC (AABC) MOALA,FERNANDO A.; DEY,SANKU. Abstract This paper takes into account the estimation for the unknown parameters of the Gompertz distribution from the frequentist and Bayesian view points by using both objective and subjective prior distributions. We first derive non-informative priors using formal rules, such as Jefreys prior and maximal data information prior (MDIP), based on Fisher information and entropy, respectively. We also propose a prior distribution that incorporate the expert’s knowledge about the issue under study. In this regard, we assume two independent gamma distributions for the parameters of the Gompertz distribution and it is employed for an elicitation process based on the predictive prior distribution by using Laplace approximation for integrals. We suppose that an... Tipo: Info:eu-repo/semantics/article Palavras-chave: Gompertz distribution; Objective prior; Jeffreys prior; Subjective prior; Maximal data information prior; Elicitation. Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000602643 Improved Bayes estimators and prediction for the Wilson-Hilferty distribution Anais da ABC (AABC) RAMOS,PEDRO L.; ALMEIDA,MARCO P.; TOMAZELLA,VERA L.D.; LOUZADA,FRANCISCO. Abstract: In this paper, we revisit the Wilson-Hilferty distribution and presented its mathematical properties such as the r-th moments and reliability properties. The parameters estimators are discussed using objective reference Bayesian analysis for both complete and censored data where the resulting marginal posterior intervals have accurate frequentist coverage. A simulation study is presented to compare the performance of the proposed estimators with the frequentist approach where it is observed a clear advantage for the Bayesian method. Finally, the proposed methodology is illustrated on three real datasets. Tipo: Info:eu-repo/semantics/article Palavras-chave: Bayesian analysis; Bayesian prediction; Censored data; Objective prior; Wilson-Hilferty distribution.. Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000500202 Registros recuperados: 2 Primeira ... 1 ... Última

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