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A directed grey incidence model based on panel data

A directed grey incidence model based on panel data The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.Design/methodology/approachFirstly, this paper introduces the concept of a negative matrix and preprocesses the data of each indicator matrix to eliminate differences in dimensions and magnitudes between indicators. Then a model is constructed to measure the incidence direction and degree between indicators, and the properties of the model are studied. Finally, the model is applied to a practical problem.FindingsThe grey-directed incidence degree is 1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a positive linear relationship. This degree is −1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a negative linear relationship.Practical implicationsThe example shows the number of days with good air quality is negatively correlated with the annual average concentration of each pollutant index. PM2.5, PM10 and O3 are the main pollutants affecting air quality in northern Henan.Originality/valueThis paper introduces the negative matrix and constructs a model from the holistic perspective to measure the incidence direction and level between indicators. This model can effectively measure the incidence between the feature indicator and factor indicator by integrating information from the point, row, column and matrix. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Grey Systems Theory and Application Emerald Publishing

A directed grey incidence model based on panel data

Zhai, Yanli; Luo, Gege; Luo, Dang
Grey Systems Theory and Application , Volume 14 (4): 21 – Sep 24, 2024
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References (35)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2043-9377
DOI
10.1108/gs-02-2024-0025
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.Design/methodology/approachFirstly, this paper introduces the concept of a negative matrix and preprocesses the data of each indicator matrix to eliminate differences in dimensions and magnitudes between indicators. Then a model is constructed to measure the incidence direction and degree between indicators, and the properties of the model are studied. Finally, the model is applied to a practical problem.FindingsThe grey-directed incidence degree is 1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a positive linear relationship. This degree is −1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a negative linear relationship.Practical implicationsThe example shows the number of days with good air quality is negatively correlated with the annual average concentration of each pollutant index. PM2.5, PM10 and O3 are the main pollutants affecting air quality in northern Henan.Originality/valueThis paper introduces the negative matrix and constructs a model from the holistic perspective to measure the incidence direction and level between indicators. This model can effectively measure the incidence between the feature indicator and factor indicator by integrating information from the point, row, column and matrix.

Journal

Grey Systems Theory and Application – Emerald Publishing

Published: Sep 24, 2024

Keywords: Panel data; Negative matrix; Positive incidence degree; Directed incidence degree

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