A theory of truncated inverse sampling. Issue 4 (2nd October 2018)

• Record Type: Journal Article
• Authors: Chen, Xinjia
• Is Part Of: Sequential analysis. Volume 37:Issue 4(2018)
• Page Start: 455
• Page End: 486
• Publication Date: 2018-10-02
• Subjects: Truncated inverse sampling -- Monte Carlo estimation -- nonasymptotic method -- sequential estimation -- confidence interval -- Uncertainty -- Bounded random variable -- Random walk; 62L12 -- 62D05; Sequential analysis -- Periodicals; 519.54
• DOI: 10.1080/07474946.2018.1554888
• Languages: English
• ISSNs: 0747-4946

Abstract

Abstract: In this paper, we have established a new theory of truncated inverse sampling for estimating mean values of non-negative random variables such as binomial, Poisson, hyper-geometrical, and bounded variables. We have derived explicit formulas and computational methods for designing sampling schemes to ensure prescribed levels of precision and confidence for point estimators. Moreover, we have developed interval estimation methods following truncated inverse sampling procedures.