EconPapers    
Economics at your fingertips  
 

Characterization of the Geometric Distribution Via Linear Combinations of Observations and of Records

Barry C. Arnold () and Jose A. Villasenor
Additional contact information
Barry C. Arnold: University of California Riverside
Jose A. Villasenor: Colegio de Postgraduados

Sankhya A: The Indian Journal of Statistics, 2023, vol. 85, issue 1, No 26, 657 pages

Abstract: Abstract In a sequence of independent identically distributed geometric random variables, the sum of the first two record values is distributed as a simple linear combination of geometric variables. It is verified that this distributional property characterizes the geometric distribution. A related characterization conjecture is also discussed. Related discussion in the context of weak records is also provided.

Keywords: Upper records; convolution; record spacings; weak records.; Primary 60E05; Secondary 62E10 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13171-021-00271-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sankha:v:85:y:2023:i:1:d:10.1007_s13171-021-00271-2

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/13171

DOI: 10.1007/s13171-021-00271-2

Access Statistics for this article

Sankhya A: The Indian Journal of Statistics is currently edited by Dipak Dey

More articles in Sankhya A: The Indian Journal of Statistics from Springer, Indian Statistical Institute
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:sankha:v:85:y:2023:i:1:d:10.1007_s13171-021-00271-2