EDA on the asymptotic normality of the standardized sequential stopping times, Part-II: Distribution-free models. Issue 3 (2nd July 2020)

• Record Type: Journal Article
• Authors: Mukhopadhyay, Nitis; Zhang, Chen
• Is Part Of: Sequential analysis. Volume 39:Issue 3(2020)
• Page Start: 367
• Page End: 398
• Publication Date: 2020-07-02
• Subjects: Asymptotics -- exploratory data analysis -- fixed-width confidence interval -- mean estimation -- minimum risk point estimation -- nonparametrics -- squared error loss -- standardized stopping time -- unknown distribution -- variance estimation; 62L12 -- 62L10 -- 62E17; Sequential analysis -- Periodicals; 519.54
• DOI: 10.1080/07474946.2020.1823193
• Languages: English
• ISSNs: 0747-4946

Abstract

Abstract: In sequential analysis, an experimenter gathers information regarding an unknown functional (parameter) by observing random samples in successive steps. We discuss a number of distribution-free scenarios under a variety of loss functions. The number of observations gathered upon termination is a positive integer-valued random variable, customarily denoted by N . Often, a standardized version of N would follow an approximate normal distribution in the asymptotic sense. We provide exploratory data analysis (EDA) with the help of a number of interesting illustrations. We do so via large-scale simulation studies to demonstrate broad applicability of the purely sequential methodologies along with the appropriateness of asymptotic normality of the standardized stopping variables as a practical and useful guideline.