Progressively Type-II censored competing risks data from the linear exponential distribution

Abstract

Across different types of lifetime studies, whether it be in the medical or engineering sciences, the possibility of competing causes of failures needs to be addressed. Typically referred to as competing risks, in this article we consider progressively type-II censored competing risks data when the lifetimes are assumed to come from a linear exponential distribution. We develop likelihood inference and demonstrate the performance of the estimators via an extensive Monte Carlo simulation study. We also provide an illustrative example using a small data set.

Keywords:

• Competing risks
• progressive censoring
• linear exponential distribution
• maximum likelihood estimation

Additional information

Funding

This article was funded by Natural Sciences and Engineering Research Council of Canada [grant number RGPIN-2015-06112].