Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

A Note on the Sampling Distribution of the Information Content of the Priority Vector of a Consistent Pairwise Comparison Judgment Matrix of AHP

V. M. Rao Tummala and H. Ling
The Journal of the Operational Research Society
Vol. 51, No. 2 (Feb., 2000), pp. 237-240
DOI: 10.2307/254264
Stable URL: http://www.jstor.org/stable/254264
Page Count: 4
  • Subscribe ($19.50)
  • Cite this Item
A Note on the Sampling Distribution of the Information Content of the Priority Vector of a Consistent Pairwise Comparison Judgment Matrix of AHP
Preview not available

Abstract

The sampling distribution of the information content (entropy) of the priority vector of a consistent pairwise comparison judgment matrix, PCJM(n) using the Analytic Hierarchy Process (AHP) is studied by Noble and Sanchez, where n is the number of criteria associated with the matrix. They concluded simulation experiments with sample size of 1000 and found that the distribution is normal for n = 4, 5,..., 15. When we increased the sample size to 2000, to 3000,..., to 8000, we found that the sampling distribution of entropy is not normal for all n, n = 4, 5,..., 15. By using BestFit software system and using sample sizes of 8000, we found that the best-fitted and the second-best-fitted distributions of the entropy are either Weibull or normal for n≥ 4. If we consider the most number of best fitted distributions as the criteria, then Weibull should be considered as the sampling distribution of the entropy for n≥ 4. For n = 3, beta should be considered as the best-fitted distribution.

Page Thumbnails

  • Thumbnail: Page 
[237]
    [237]
  • Thumbnail: Page 
238
    238
  • Thumbnail: Page 
239
    239
  • Thumbnail: Page 
240
    240