ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2212.05151
59
3
v1v2v3 (latest)

Optimal sequential tests for multiple hypotheses when sampling from a Bernoulli population

10 December 2022
A. Novikov
ArXiv (abs)PDFHTML
Abstract

In this paper we deal with the problem of sequential testing of multiple hypotheses. We are interested in minimising a weighted average sample number under restrictions on the error probabilities. A computer-oriented method of construction of optimal sequential tests is proposed. For the particular case of sampling from a Bernoulli population we develop a whole set of computer algorithms for optimal design and performance evaluation of sequential tests and implement them in the form of computer code written in R programming language. The tests we obtain are exact (neither asymptotic nor approximate). Extensions to other distribution families are discussed. A numerical comparison with other known tests (of MSPRT type) is carried out.

View on arXiv
Comments on this paper