Approximations and Inequalities for Moving Sums

Joseph Glaz (), Joseph Naus () and Xiao Wang ()
Additional contact information
Joseph Glaz: University of Connecticut
Joseph Naus: The State University of New Jersey
Xiao Wang: University of Connecticut

Methodology and Computing in Applied Probability, 2012, vol. 14, issue 3, 597-616

Abstract: Abstract In this article accurate approximations and inequalities are derived for the distribution, expected stopping time and variance of the stopping time associated with moving sums of independent and identically distributed continuous random variables. Numerical results for a scan statistic based on a sequence of moving sums are presented for a normal distribution model, for both known and unknown mean and variance. The new R algorithms for the multivariate normal and t distributions established by Genz et al. (2010) provide readily available numerical values of the bounds and approximations.

Keywords: Approximation; Moving sum; Multivariate normal; Multivariate T; Probability inequality; R algorithms; Scan statistics; Stopping time; 60E15; 60G10; 62E17; 62M07 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://link.springer.com/10.1007/s11009-011-9251-x 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:metcap:v:14:y:2012:i:3:d:10.1007_s11009-011-9251-x

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-011-9251-x

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().