摘要

The failure rate with a bathtub shape usually increases very fast in the wear-out phase. In this case, the bathtub curve model with a finite support can better adapt the sharp change in failure rate. There are few models with the finite support. This paper presents such a model. However, the maximum likelihood estimator of the location parameter of such models sometimes converges to the largest observation of a dataset. An extended maximum spacing method is developed to estimate the parameters for the case where the maximum likelihood method fails. Three examples are included to illustrate the appropriateness of the proposed model and estimation method.