{"title":"Sociophysics of income distributions modeled by deformed fermi-dirac distributions","authors":"E. Dil, E. Dil","doi":"10.1080/0022250X.2021.1973456","DOIUrl":null,"url":null,"abstract":"ABSTRACT In order to model the income data, the physical distributions of Fermi-Dirac and Bose-Einstein families have already been proposed in the literature. In this study, we generalize Fermi-Dirac distribution by using a q,p-deformed version of Fermi-Dirac distribution which provides the advantage of working with flexible free q, p deformation parameters as the regression parameters for modeling the income data. We analyze the accuracy of the generalized version, q,p-deformed Fermi-Dirac distribution, on describing the data of income share held by quintiles for countries, and household income for the states of U.S.A. in 2018. We also use minimization routine for modeling the data which leads to the best fit parameters for the deformation parameters q and p. Subsequently, we plot the fitted q,p-deformed Fermi-Dirac distribution as income distribution with the obtained deformation parameters, then find the statistical confidence values from the fitted curve. We figure out that our model properly describes the income data for the systems experiencing a high level of income inequality, and also values are correlated with the Gini index for those of considered systems.","PeriodicalId":50139,"journal":{"name":"Journal of Mathematical Sociology","volume":"47 1","pages":"97 - 122"},"PeriodicalIF":1.3000,"publicationDate":"2021-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematical Sociology","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/0022250X.2021.1973456","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT In order to model the income data, the physical distributions of Fermi-Dirac and Bose-Einstein families have already been proposed in the literature. In this study, we generalize Fermi-Dirac distribution by using a q,p-deformed version of Fermi-Dirac distribution which provides the advantage of working with flexible free q, p deformation parameters as the regression parameters for modeling the income data. We analyze the accuracy of the generalized version, q,p-deformed Fermi-Dirac distribution, on describing the data of income share held by quintiles for countries, and household income for the states of U.S.A. in 2018. We also use minimization routine for modeling the data which leads to the best fit parameters for the deformation parameters q and p. Subsequently, we plot the fitted q,p-deformed Fermi-Dirac distribution as income distribution with the obtained deformation parameters, then find the statistical confidence values from the fitted curve. We figure out that our model properly describes the income data for the systems experiencing a high level of income inequality, and also values are correlated with the Gini index for those of considered systems.
期刊介绍:
The goal of the Journal of Mathematical Sociology is to publish models and mathematical techniques that would likely be useful to professional sociologists. The Journal also welcomes papers of mutual interest to social scientists and other social and behavioral scientists, as well as papers by non-social scientists that may encourage fruitful connections between sociology and other disciplines. Reviews of new or developing areas of mathematics and mathematical modeling that may have significant applications in sociology will also be considered.
The Journal of Mathematical Sociology is published in association with the International Network for Social Network Analysis, the Japanese Association for Mathematical Sociology, the Mathematical Sociology Section of the American Sociological Association, and the Methodology Section of the American Sociological Association.