Fuzzy simple linear regression using Gaussian membership functions minimization problem
Under the additional assumption that the errors are normally distributed, the Ordinary Least Squares (OLS) method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the OLS method based on a so-called Gaussian membership funct...
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| Format: | Article |
| Language: | English |
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Ayandegan Institute of Higher Education,
2022-10-01
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| Series: | Journal of Fuzzy Extension and Applications |
| Subjects: | |
| Online Access: | https://www.journal-fea.com/article_155107_24583b21a95541723ceb8e7bc158641e.pdf |
| _version_ | 1797787153246191616 |
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| author | Besma Belhadj |
| author_facet | Besma Belhadj |
| author_sort | Besma Belhadj |
| collection | DOAJ |
| description | Under the additional assumption that the errors are normally distributed, the Ordinary Least Squares (OLS) method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the OLS method based on a so-called Gaussian membership function, one that checks the validity of the verbal explanation suggested by the observer. The fuzzy estimation approach demonstrated here is based on a suitable framework for a natural behavior observed in nature. An application based on a group of MENA countries in 2015 is presented to estimate the employment poverty relationship.Under the additional assumption that the errors are normally distributed, the ordinary least squares method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the ordinary least squares method based on a so-called Gaussian membership function, one that checks the validity of the verbal explanation suggested by the observer. The fuzzy estimation approach demonstrated here is based on a suitable framework for a natural behavior observed in nature. An application based on a group of MENA countries in 2015 is presented to estimate the Employment Poverty relationship. |
| first_indexed | 2024-03-13T01:18:52Z |
| format | Article |
| id | doaj.art-d5651f7c2f6044758b15ec0f6acbcb2e |
| institution | Directory Open Access Journal |
| issn | 2783-1442 2717-3453 |
| language | English |
| last_indexed | 2024-03-13T01:18:52Z |
| publishDate | 2022-10-01 |
| publisher | Ayandegan Institute of Higher Education, |
| record_format | Article |
| series | Journal of Fuzzy Extension and Applications |
| spelling | doaj.art-d5651f7c2f6044758b15ec0f6acbcb2e2023-07-05T06:42:19ZengAyandegan Institute of Higher Education,Journal of Fuzzy Extension and Applications2783-14422717-34532022-10-013427928910.22105/jfea.2022.345298.1222155107Fuzzy simple linear regression using Gaussian membership functions minimization problemBesma Belhadj0LaREQuaD, FSEGT, University of ElManar, Tunisia.Under the additional assumption that the errors are normally distributed, the Ordinary Least Squares (OLS) method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the OLS method based on a so-called Gaussian membership function, one that checks the validity of the verbal explanation suggested by the observer. The fuzzy estimation approach demonstrated here is based on a suitable framework for a natural behavior observed in nature. An application based on a group of MENA countries in 2015 is presented to estimate the employment poverty relationship.Under the additional assumption that the errors are normally distributed, the ordinary least squares method is the maximum likelihood estimator. In this paper, we propose, for a simple regression, an estimation method alternative to the ordinary least squares method based on a so-called Gaussian membership function, one that checks the validity of the verbal explanation suggested by the observer. The fuzzy estimation approach demonstrated here is based on a suitable framework for a natural behavior observed in nature. An application based on a group of MENA countries in 2015 is presented to estimate the Employment Poverty relationship.https://www.journal-fea.com/article_155107_24583b21a95541723ceb8e7bc158641e.pdfmathematical modelingfuzzy regressiongaussian fuzzy responsesgaussian membership function |
| spellingShingle | Besma Belhadj Fuzzy simple linear regression using Gaussian membership functions minimization problem Journal of Fuzzy Extension and Applications mathematical modeling fuzzy regression gaussian fuzzy responses gaussian membership function |
| title | Fuzzy simple linear regression using Gaussian membership functions minimization problem |
| title_full | Fuzzy simple linear regression using Gaussian membership functions minimization problem |
| title_fullStr | Fuzzy simple linear regression using Gaussian membership functions minimization problem |
| title_full_unstemmed | Fuzzy simple linear regression using Gaussian membership functions minimization problem |
| title_short | Fuzzy simple linear regression using Gaussian membership functions minimization problem |
| title_sort | fuzzy simple linear regression using gaussian membership functions minimization problem |
| topic | mathematical modeling fuzzy regression gaussian fuzzy responses gaussian membership function |
| url | https://www.journal-fea.com/article_155107_24583b21a95541723ceb8e7bc158641e.pdf |
| work_keys_str_mv | AT besmabelhadj fuzzysimplelinearregressionusinggaussianmembershipfunctionsminimizationproblem |