2008/10/30 by Xinjia Chen, Chen, Xinjia
Computer Science · Decision Sciences · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Probabilistic and Robust Engineering Design #Probability (math.PR) #Statistical Methods and Inference #Statistics Theory (math.ST) #cs.LG #math.PR #math.ST #stat.ME #stat.TH
paper · pdf · doi:10.48550/arxiv.0810.5551
31 pages, no figure, revised proofs
openalex publication_date 2008/10/30 · arxiv created 2008/11/11 · arxiv updated 2013/11/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we have established a new framework 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.