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Incomplete pairwise comparison matrices are increasingly employed to save resources and reduce cognitive load by collecting only a subset of all possible pairwise comparisons. We present their graph representation and some completion…

Optimization and Control · Mathematics 2026-03-30 László Csató , Sándor Bozóki

This article explores a relationship between inconsistency in the pairwise comparisons method and conditions of order preservation. A pairwise comparisons matrix with elements from an alo-group is investigated. This approach allows for a…

Discrete Mathematics · Computer Science 2019-03-29 Konrad Kulakowski , Jiri Mazurek , Jaroslav Ramik , Michael Soltys

Reasoning with fuzzy sets can be achieved through measures such as similarity and distance. However, these measures can often give misleading results when considered independently, for example giving the same value for two different pairs…

Artificial Intelligence · Computer Science 2014-09-04 Josie McCulloch , Christian Wagner , Uwe Aickelin

A common problem in numerous research areas, particularly in clinical trials, is to test whether the effect of an explanatory variable on an outcome variable is equivalent across different groups. In practice, these tests are frequently…

Methodology · Statistics 2024-05-03 Niklas Hagemann , Kathrin Möllenhoff

We propose a generalised framework for the updating of a prior ensemble to a posterior ensemble, an essential yet challenging part in ensemble-based filtering methods. The proposed framework is based on a generalised and fully Bayesian view…

Methodology · Statistics 2021-03-29 Margrethe Kvale Loe , Håkon Tjelmeland

Calibration is a pivotal aspect in predictive modeling, as it ensures that the predictions closely correspond with what we observe empirically. The contemporary calibration framework, however, is predominantly focused on prediction models…

Methodology · Statistics 2023-09-18 Bavo De Cock Campo

Pairwise comparison models have been widely used for utility evaluation and rank aggregation across various fields. The increasing scale of modern problems underscores the need to understand statistical inference in these models when the…

Statistics Theory · Mathematics 2025-12-16 Ruijian Han , Wenlu Tang , Yiming Xu

We propose randomized confidence intervals based on the Neyman-Pearson lemma, in order to make them more broadly applicable to distributions that do not satisfy regularity conditions. This is achieved by using the definition of fuzzy…

Recently, there has been much research into modelling of uncertainty in human perception through Fuzzy Sets (FSs). Most of this research has focused on allowing respondents to express their (intra) uncertainty using intervals. Here,…

Artificial Intelligence · Computer Science 2019-07-11 Javier Navarro , Christian Wagner

Generally any real-world problem is not always solvable, because in that not only a percentage of uncertainty is present, but also, a certain percentage of indeterminacy is present. The presence of uncertainty has been analyzed using fuzzy…

General Mathematics · Mathematics 2007-05-23 W. B. Vasantha Kandasamy , Florentin Smarandache , K. Ilanthenral

We investigate an application of a mathematically robust minimization method -- the gradient method -- to the consistencization problem of a pairwise comparisons (PC) matrix. Our approach sheds new light on the notion of a priority vector…

Rings and Algebras · Mathematics 2022-07-19 Jean-Pierre Magnot , Jiří Mazurek , Viera Čerňanová

To obtain reliable results of expertise, which usually use individual and group expert pairwise comparisons, it is important to summarize (aggregate) expert estimates provided that they are sufficiently consistent. There are several ways to…

Methodology · Statistics 2024-10-07 Vitaliy Tsyganok , Andriy Olenko , Pavlo Roik , Oksana Vlasenko

Many modern data sets require inference methods that can estimate the shared and individual-specific components of variability in collections of matrices that change over time. Promising methods have been developed to analyze these types of…

Methodology · Statistics 2019-04-30 Arkaprava Roy , Jana Schaich-Borg , David B Dunson

In several multiobjective decision problems Pairwise Comparison Matrices (PCM) are applied to evaluate the decision variants. The problem that arises very often is the inconsistency of a given PCM. In such a situation it is important to…

Optimization and Control · Mathematics 2024-12-10 Marcin Anholcer , Janos Fülöp

Comparing competing mathematical models of complex natural processes is a shared goal among many branches of science. The Bayesian probabilistic framework offers a principled way to perform model comparison and extract useful metrics for…

This study presents special cases of inconsistent pairwise comparisons PC matrices and analysis of their eigenvalue-based inconsistency index using mathematical methods. All studied special cases of PC matrices are Toeplitz matrices with…

Optimization and Control · Mathematics 2019-08-01 Viera Čerňanová , Waldemar W. Koczkodaj

Predictions of uncertainty-aware models are diverse, ranging from single point estimates (often averaged over prediction samples) to predictive distributions, to set-valued or credal-set representations. We propose a novel unified…

Machine Learning · Computer Science 2025-02-18 Shireen Kudukkil Manchingal , Muhammad Mubashar , Kaizheng Wang , Fabio Cuzzolin

The aim of the present article is to introduce a concept which allows to generalise the notion of Poissonian pair correlation, a second-order equidistribution property, to higher dimensions. Roughly speaking, in the one-dimensional setting,…

Number Theory · Mathematics 2018-09-18 Aicke Hinrichs , Lisa Kaltenböck , Gerhard Larcher , Wolfgang Stockinger , Mario Ullrich

In this paper we consider the collaborative ranking setting: a pool of users each provides a small number of pairwise preferences between $d$ possible items; from these we need to predict preferences of the users for items they have not yet…

Machine Learning · Statistics 2015-07-17 Dohyung Park , Joe Neeman , Jin Zhang , Sujay Sanghavi , Inderjit S. Dhillon

In this paper, a new interval type-2 fuzzy neural network able to construct non-separable fuzzy rules with adaptive shapes is introduced. To reflect the uncertainty, the shape of fuzzy sets considered to be uncertain. Therefore, a new form…

Machine Learning · Computer Science 2021-12-22 Armin Salimi-Badr