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Journal of Statistical Computation and Simulation Volume 77, 2007 - Issue 7
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Original Articles

Adjusted profile likelihoods for the weibull shape parameter

Silvia L. P. Ferrari Departamento de Estatística, IME, Universidade de São Paulo, Caixa Postal 66281, São Paulo/SP, 05311–970, BrazilCorrespondence[email protected]
,
Michel Ferreira Da Silva Departmento de Estatística, ICEX, Universidade Federal de Minas Gerais, Campus Pampulha, Belo Horizonte/MG, 31270-901, Brazil
&
Francisco Cribari–neto Departamento de Estatística, CCEN, Universidade Federal de Pernambuco, Cidade Universitária, Recife/PE, 50740–540, Brazil
Pages 531-548 | Received 23 Mar 2005, Published online: 01 Aug 2007

Citations (7)

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Michel Ferreira Da Silva, SilviaL. P. Ferrari & Francisco Cribari–Neto. (2008) Improved likelihood inference for the shape parameter in Weibull regression. Journal of Statistical Computation and Simulation 78:9, pages 789-811.
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Articles from other publishers (6)

Ayman Baklizi. (2022) Refined Inference on the Scale Parameter of the Generalized Logistic Distribution Based on Adjusted Profile Likelihood Functions. Symmetry 14:11, pages 2369.
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R. Y. Jiang, F. Q. Qi & Y. Cao. (2022) A Mode-based Approach for Lognormal Parameter Estimation on Heavily Censored Data. A Mode-based Approach for Lognormal Parameter Estimation on Heavily Censored Data.
Markus Chagas Stein, Michel Ferreira da Silva & Luiz Henrique Duczmal. (2014) Alternatives to the usual likelihood ratio test in mixed linear models. Computational Statistics & Data Analysis 69, pages 184-197.
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Xiaoyi Min & Dongchu Sun. (2012) A matching prior based on the modified profile likelihood in a generalized Weibull stress‐strength model. Canadian Journal of Statistics 41:1, pages 83-97.
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Young-Ju Kim. (2011) A comparative study of nonparametric estimation in Weibull regression: A penalized likelihood approach. Computational Statistics & Data Analysis 55:4, pages 1884-1896.
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Zhenlin Yang & Dennis K. J. Lin. (2007) Improved maximum‐likelihood estimation for the common shape parameter of several Weibull populations. Applied Stochastic Models in Business and Industry 23:5, pages 373-383.
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