Statistical analysis of competing risks model from Marshall–Olkin extended Chen distribution under adaptive progressively interval censoring with random removals

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.

Keywords:

• Adaptive progressively interval censoring scheme
• competing risks
• Marshall–Olkin extended Chen distribution
• EM algorithm
• bootstrap confidence intervals
• likelihood ratio tests

Additional information

Funding

This work is supported by the National Natural Science Foundation of China (71571144, 71401134, 71171164, 11701406).