Controlling Bivariate Categorical Processes using Scan Rules

Sotirios Bersimis (), Athanasios Sachlas () and Philippe Castagliola ()
Additional contact information
Sotirios Bersimis: University of Piraeus
Athanasios Sachlas: University of Piraeus
Philippe Castagliola: LUNAM Université, Université de Nantes & IRCCyN UMR CNRS 6597

Methodology and Computing in Applied Probability, 2017, vol. 19, issue 4, 1135-1149

Abstract: Abstract In this paper, we introduce a methodology for efficiently monitoring a health process that classify the intervention outcome, in two dependent characteristics, as “absolutely successful”, “with minor but acceptable complications” and “unsuccessful due to severe complications”. The monitoring procedure is based on appropriate 2-dimensional scan rules. The run length distribution is acquired by studying the waiting time distribution for the first occurrence of a 2-dimensional scan in a bivariate sequence of trinomial trials. The waiting time distribution is derived through a Markov chain embedding technique. The proposed procedure is applied on two simulated cases while it is tested against a competing method showing an excellent performance.

Keywords: Multi-attribute processes; Markov chain embeddable random variables; Multivariate statistical process control; Waiting time distributions; 60E05; 60J10 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11009-016-9508-5 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:19:y:2017:i:4:d:10.1007_s11009-016-9508-5

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

DOI: 10.1007/s11009-016-9508-5

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 ().