Some Notes on the Similarity of Priority Vectors Derived by the Eigenvalue Method and the Geometric Mean Method

03/11/2022
by   Jiri Mazurek, et al.
0

The aim of this paper is to examine the differences in ordinal rankings obtained from a pairwise comparison matrix using the eigenvalue method and the geometric mean method. We introduce several propositions on the (dis)similarity of both rankings with respect to the matrix size and its inconsistency expressed by the Koczkodaj's inconsistency index. Further on, we examine the relationship between differences in both rankings and Kendall's rank correlation coefficient τ and Spearman's rank coefficient ρ. Apart from theoretical results, intuitive numerical examples and Monte Carlo simulations are provided as well.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/09/2020

On the similarity between ranking vectors in the pairwise comparison method

There are many priority deriving methods for pairwise comparison matrice...
research
09/13/2021

The correlation coefficient between citation metrics and winning a Nobel or Abel Prize

Computing such correlation coefficient would be straightforward had we h...
research
07/01/2018

Antithetic and Monte Carlo kernel estimators for partial rankings

In the modern age, rankings data is ubiquitous and it is useful for a va...
research
11/22/2019

Satisfaction of the Condition of Order Preservation: A Simulation Study

We examine satisfaction of the condition of order preservation (COP) wit...
research
08/06/2023

Semilinear elliptic eigenvalue problem: Parametric analyticity and the uncertainty quantification

In this paper, to the best of our knowledge, we make the first attempt a...
research
08/31/2017

Quality Enhancement by Weighted Rank Aggregation of Crowd Opinion

Expertise of annotators has a major role in crowdsourcing based opinion ...

Please sign up or login with your details

Forgot password? Click here to reset