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Principal component analysis and factor analysis are fundamental multivariate analysis methods. In this paper a unified framework to connect them is introduced. Under a general latent variable model, we present matrix optimization problems…

Methodology · Statistics 2024-05-31 Shifeng Xiong

In a typical Internet-of-Things setting that involves scientific applications, a target computation can be evaluated in many different ways depending on the split of computations among various devices. On the one hand, different…

Performance · Computer Science 2022-08-09 Aravind Sankaran , Paolo Bientinesi

A new look on the principal component analysis has been presented. Firstly, a geometric interpretation of determination coefficient was shown. In turn, the ability to represent the analyzed data and their interdependencies in the form of…

Methodology · Statistics 2017-11-29 Zenon Gniazdowski

In this paper, we propose a new model that allows us to investigate this competitive aspect of real networks in quantitative terms. Through theoretical analysis and numerical simulations, we find that the competitive network have the…

Physics and Society · Physics 2015-05-05 Jin-Li Guo , Chao Fan , Ya-Li Ji

The article discusses selected problems related to both principal component analysis (PCA) and factor analysis (FA). In particular, both types of analysis were compared. A vector interpretation for both PCA and FA has also been proposed.…

Machine Learning · Computer Science 2021-10-22 Zenon Gniazdowski

Many nations are adopting higher education strategies that emphasize the development of elite universities able to compete at the international level in the attraction of skills and resources. Elite universities pursue excellence in all…

Digital Libraries · Computer Science 2018-10-31 Giovanni Abramo , Ciriaco Andrea D'Angelo , Flavia Di Costa

Assessing the research performance of multi-disciplinary institutions, where scientists belong to many fields, requires that the evaluators plan how to aggregate the performance measures of the various fields. Two methods of aggregation are…

Digital Libraries · Computer Science 2018-10-31 Giovanni Abramo , Ciriaco Andrea D'Angelo

Ranking is a natural and ubiquitous way to facilitate decision-making in various applications. However, different rankings are often used for the same set of entities, with each ranking method placing emphasis on different factors. These…

Human-Computer Interaction · Computer Science 2020-04-15 Abishek Puri , Bon Kyung Ku , Yong Wang , Huamin Qu

This article presents the results of a cluster analysis of the regions of the Russian Federation in terms of the main parameters of socio-economic development according to the data presented in the official data sources of the Federal State…

We introduce a novel class of factor analysis methodologies for the joint analysis of multiple studies. The goal is to separately identify and estimate 1) common factors shared across multiple studies, and 2) study-specific factors. We…

Applications · Statistics 2018-06-27 Roberta De Vito , Ruggero Bellio , Lorenzo Trippa , Giovanni Parmigiani

This paper describes a generalizable model evaluation method that can be adapted to evaluate AI/ML models across multiple criteria including core scientific principles and more practical outcomes. Emerging from prediction competitions in…

Machine Learning · Computer Science 2024-03-19 Jason L. Harman , Jaelle Scheuerman

Increasing investments into various dimensions of sports draw a significant amount of attention to the way these resources are being managed and which organizations achieve development goals with higher efficiency. This paper reviews the…

Economics · Quantitative Finance 2016-12-23 Ilya Solntsev , Anatoly Vorobyev , Elnura Irmatova , Nikita Osokin

The M6 Competition assessed the performance of competitors using a ranked probability score and an information ratio (IR). While these metrics do well at picking the winners in the competition, crucial questions remain for investors with…

Portfolio Management · Quantitative Finance 2024-08-13 Matthew J. Schneider , Rufus Rankin , Prabir Burman , Alexander Aue

We propose a new performance indicator to evaluate the productivity of research institutions by their disseminated scientific papers. The new quality measure includes two principle components: the normalized impact factor of the journal in…

Instrumentation and Methods for Astrophysics · Physics 2015-08-18 S. Bilir , E. Gogus , O. Onal Tas , T. Yontan

Principal component analysis (PCA) is a widely used method for data processing, such as for dimension reduction and visualization. Standard PCA is known to be sensitive to outliers, and thus, various robust PCA methods have been proposed.…

Machine Learning · Statistics 2020-08-11 Keishi Sando , Hideitsu Hino

Performance measurement in competitive domains is frequently confounded by shared environmental factors that obscure true performance differences. For instance, absolute metrics can be heavily influenced by factors as varied as weather…

Data Analysis, Statistics and Probability · Physics 2025-04-29 M. R. Brown , G. Scott , L. Kilduff

The article presents the results of multivariate classification of Russian regions by the indicators characterizing the population income and their concentration. The clusterization was performed upon an author approach to selecting the…

General Economics · Economics 2020-10-16 Natalia A. Sadovnikova , Olga A. Zolotareva

Being one of the most important factors of economic growth of the country, innovations became one of the key vectors in Russian economic policy. In this field technology parks are one of the most effective instruments which can provide…

General Finance · Quantitative Finance 2014-02-24 Anna V. Vilisova , Qiang Fu

University evaluation is a topic of increasing concern in Italy as well as in other countries. In empirical analysis, university activities and performances are generally measured by means of indicator variables, summarizing the available…

Applications · Statistics 2014-04-25 Valentina Raponi , Francesca Martella , Antonello Maruotti

Although machine learning approaches have been widely used in the field of finance, to very successful degrees, these approaches remain bespoke to specific investigations and opaque in terms of explainability, comparability, and…

Trading and Market Microstructure · Quantitative Finance 2022-06-22 Artur Sokolovsky , Luca Arnaboldi