On Robustifying of the Sequential Probability Ratio Test for a Discrete Model under “Contaminations”

Abstract

The problem of robustifying of the sequential probability ratio test is considered for a discrete hypothetical model. Exact values for error probabilities and for conditional expected sample sizes are obtained. Asymptotic robustness analysis for these characteristics is performed under “contaminations”. A two-parametric family of modified sequential probability ratio tests is proposed and analyzed to get the robust test by the minimax risk criterion. Numerical experiments illustrate the theoretical results.