A class of tests for new better than used in expectation with incomplete data

DOI10.1080/07474948608836110zbMath0621.62029OpenAlexW2043204765MaRDI QIDQ3757161

Yoshiki Kumazawa

Publication date: 1986

Published in: Sequential Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07474948608836110

zbMATH Keywords

asymptotic normalitynew better than used in expectationcounting process theoryNBUEincomplete observationsrandomly censoredlocally most powerful testssequence of contiguous alternativesmartingale weak convergence theoremsvon Mises' statistical functional

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Asymptotic properties of parametric tests (62F05) Reliability and life testing (62N05)

Cites Work

• Unnamed Item
• Large sample behaviour of the product-limit estimator on the whole line
• On testing whether new is better than used using randomly censored data
• Testing whether new better than used in expectation for random censorship for random censorship
• Testing for New Better than Used in Expectation with Incomplete Data
• Linear Nonparametric Tests for Comparison of Counting Processes, with Applications to Censored Survival Data, Correspondent Paper
• Some Reliability Applications of the Hazard Transform

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