Inference of progressively censored competing risks data from Kumaraswamy distributions

作者：

Highlights：

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• Inference for different and common competing risks parameters is considered.

• Maximum likelihood estimators are established.

• Confidence intervals are proposed via observed fisher information matrix.

• Bayesian estimates are derived via MCMC sampling method.

• Data example on football game proportion time is illustrated.

摘要

•Inference for different and common competing risks parameters is considered.•Maximum likelihood estimators are established.•Confidence intervals are proposed via observed fisher information matrix.•Bayesian estimates are derived via MCMC sampling method.•Data example on football game proportion time is illustrated.

论文关键词：62F10,62F12,Kumaraswamy distribution,Competing risks,Progressive censoring,Maximum likelihood estimation,Bayesian estimation,Monte-Carlo simulation

论文评审过程：Received 18 August 2017, Revised 10 April 2018, Available online 16 May 2018, Version of Record 31 May 2018.

论文官网地址：https://doi.org/10.1016/j.cam.2018.05.013