Marshall Olkin Distribution
Mostrando 1-4 de 4 artigos, teses e dissertações.
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1. A new class of lifetime models and the evaluation of the confidence intervals by double percentile bootstrap
Abstract: In this paper, we introduce a new three-parameter distribution by compounding the Nadarajah-Haghighi and geometric distributions, which can be interpreted as a truncated Marshall-Olkin extended Weibull. The compounding procedure is based on the work by Marshall and Olkin 1997. We prove that the new distribution can be obtained as a compound model w
An. Acad. Bras. Ciênc.. Publicado em: 08/04/2019
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2. Parameter induction in continuous univariate distributions: Well-established G families
The art of parameter(s) induction to the baseline distribution has received a great deal of attention in recent years. The induction of one or more additional shape parameter(s) to the baseline distribution makes the distribution more flexible especially for studying the tail properties. This parameter(s) induction also proved helpful in improving the goodne
An. Acad. Bras. Ciênc.. Publicado em: 2015-06
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3. Testes em modelos weibull na forma estendida de Marshall-Olkin
Em analise de sobreviv^encia, a variavel resposta e, geralmente, o tempo ate a ocorr^encia de um evento de interesse, denominado tempo de falha, e a principal caracterstica de dados de sobreviv^ encia e a presenca de censura, que e a observac~ao parcial da resposta. Associados a essas informac~oes, alguns modelos ocupam uma posic~ao de destaque por sua compr
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 28/12/2011
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4. As distribuições Kumaraswamy-log-logística e Kumaraswamy-logística / Distributions Kumaraswamy-log-logistic and Kumaraswamy-logistic
In this work, are presented two new probability distributions, obtained from two generalization methods of the log-logistic distribution, with two parameters (LL (?, ?)). The first method described in Marshall e Olkin (1997) turns the new distribution, now with three parameters, called modified log-logistic distribution (LLM(v, ?, ?)). This distribution is m
Publicado em: 2010