Statistical analysis of competing risks model from Marshall–Olkin extended Chen distribution under adaptive progressively interval censoring with random removals |
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| Authors: | Xuchao Bai Yimin Shi Yiming Liu Hon Keung Tony Ng Bin Liu |
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| Institution: | 1. Department of Applied Mathematics, Northwestern Polytechnical University, Xi’an, China;2. Department of Statistical Science, Southern Methodist University, Dallas, Texas, USA;3. School of Applied Science, Taiyuan University of Science and Technology, Taiyuan, China |
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| Abstract: | In this paper, a new censoring scheme named by adaptive progressively interval censoring scheme is introduced. The competing risks data come from Marshall–Olkin extended Chen distribution under the new censoring scheme with random removals. We obtain the maximum likelihood estimators of the unknown parameters and the reliability function by using the EM algorithm based on the failure data. In addition, the bootstrap percentile confidence intervals and bootstrap-t confidence intervals of the unknown parameters are obtained. To test the equality of the competing risks model, the likelihood ratio tests are performed. Then, Monte Carlo simulation is conducted to evaluate the performance of the estimators under different sample sizes and removal schemes. Finally, a real data set is analyzed for illustration purpose. |
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| Keywords: | Adaptive progressively interval censoring scheme competing risks Marshall–Olkin extended Chen distribution EM algorithm bootstrap confidence intervals likelihood ratio tests |
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