Back

Convergence of unforced errors in the matching problem.

  • Published In: Statistica Neerlandica, 2024, v. 78, n. 4. P. 796 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Vidal, Ignacio 3 of 3

Abstract

The Central Limit Theorem (CLT) is a fundamental result in probability theory with numerous applications in various disciplines. There are a wide variety of CLT‐like theorems, for example the De Moivre–Laplace, Lindeberg and Lyapounov theorems. Independent and identically distributed random variables with a finite second moment are usually considered assumptions in CLTs. However, in this article we present a CLT for a sum of dependent and nonidentically distributed Bernoulli random variables that arises in the well‐known matching experiment. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Statistica Neerlandica. 2024/11, Vol. 78, Issue 4, p796
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2024
  • ISSN:0039-0402
  • DOI:10.1111/stan.12363
  • Accession Number:180926196
  • Copyright Statement:Copyright of Statistica Neerlandica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.