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Heteroscedastic log-exponentiated Weibull regression model

Author

Listed:
  • Edwin M. M. Ortega
  • Artur J. Lemonte
  • Gauss M. Cordeiro
  • Vicente G. Cancho
  • Fábio L. Mialhe

Abstract

We introduce a new class of heteroscedastic log-exponentiated Weibull (LEW) regression models. The class of regression models can be applied to censored data and be used more effectively in survival analysis. Maximum likelihood estimation of the model parameters with censored data as well as influence diagnostics for the new regression model is investigated. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the heteroscedastic LEW regression model. The normal curvatures for studying local influence are derived under various perturbation schemes. An empirical application to a real data set is provided to illustrate the usefulness of the new class of heteroscedastic regression models.

Suggested Citation

  • Edwin M. M. Ortega & Artur J. Lemonte & Gauss M. Cordeiro & Vicente G. Cancho & Fábio L. Mialhe, 2018. "Heteroscedastic log-exponentiated Weibull regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(3), pages 384-408, February.
    • Handle: RePEc:taf:japsta:v:45:y:2018:i:3:p:384-408
    DOI: 10.1080/02664763.2016.1277192
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    References listed on IDEAS

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    1. Vasconcellos, Klaus L.P. & Zea Fernandez, L.M., 2009. "Influence analysis with homogeneous linear restrictions," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3787-3794, September.
    2. Matos, Larissa A. & Lachos, Victor H. & Balakrishnan, N. & Labra, Filidor V., 2013. "Influence diagnostics in linear and nonlinear mixed-effects models with censored data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 450-464.
    3. Artur J. Lemonte & Alexandre G. Patriota, 2011. "Influence diagnostics in Birnbaum--Saunders nonlinear regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 871-884, February.
    4. Li, Ai-Ping & Chen, Zhao-Xia & Xie, Feng-Chang, 2012. "Diagnostic analysis for heterogeneous log-Birnbaum–Saunders regression models," Statistics & Probability Letters, Elsevier, vol. 82(9), pages 1690-1698.
    5. Li, Ai-Ping & Xie, Feng-Chang, 2012. "Diagnostics for a class of survival regression models with heavy-tailed errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4204-4214.
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    Cited by:

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