Study of Optimal Adaptive Rule in Testing Composite Hypothesis

Abstract

In this article on sequential adaptive testing, we have studied the optimal allocation between two populations for testing a composite hypothesis involving the parameters, with the goal of decreasing allocation of one of the treatments to the order of the logarithm of the sample size while decreasing the probability of incorrect selection to zero. We have proved the result for large sample sizes both mathematically and by simulation studies.

Keywords:

• Adaptive allocation
• Average sample number
• Composite hypothesis
• Conditional log-likelihood
• Log-likelihood
• Probability of incorrect selection

Subject Classifications:

• 93C99

ACKNOWLEDGMENT

We appreciate the comments made by the Associate Editor and the referee.

Notes

Recommended by Nitis Mukhopadhyay