Departure-based Asymptotic Stochastic Order for Random Processes

2021/03/02 by Sugata Ghosh, Asok K. Nanda, Ghosh, Sugata +1
Computer Science · Mathematics · #60E15 #60G07 #62G30 #Applications (stat.AP) #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Methodology (stat.ME) #Probability (math.PR) #Statistical Distribution Estimation and Applications #Statistics Theory (math.ST) #Target Tracking and Data Fusion in Sensor Networks #math.PR #math.ST #msc:60E15 #msc:60G07 #msc:62G30 #stat.AP #stat.ME #stat.TH

paper · pdf · doi:10.48550/arxiv.2103.01727

33 pages, reference hyperlink added

openalex publication_date 2021/03/02 · arxiv created 2021/03/03 · arxiv updated 2021/03/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We propose and analyze a specific asymptotic stochastic order for random processes based on the measure of departure discussed in the literature. As applications, we stochastically compare mixtures of order statistics and record values coming from two different homogeneous samples, as the sample size becomes large.

Citations

• Asymptotic Stochastic Comparison of Random Processes

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