Progressive censoring under inverse sampling for nonparametric two-sample problems

Abstract

The object of the present investigation is to provide suitable nonparametric tests for the identity of two univariate populations when there is a random sample of fixed size from one of the populations and the observations from the second population are drawn sequentially by an inverse binomial sampling. A progressive censoring test procedure corresponding to the inverse binomial sample is proposed. Different large sample results of the proposed tests are formulated and examined.

Keywords:

• Inverse sampling
• distribution free
• local alternatives
• weak convergence
• tightness
• progressive censoring