Generalized Ridge Regression: Applications to Nonorthogonal Linear Regression Models
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866913783493951488 |
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| author | Gómez, Román Salmerón García, Catalina García Reina, Guillermo Hortal |
| author_facet | Gómez, Román Salmerón García, Catalina García Reina, Guillermo Hortal |
| contents | This paper analyzes the possibilities of using the generalized ridge regression to mitigate multicollinearity in a multiple linear regression model. For this purpose, we obtain the expressions for the estimated variance, the coefficient of variation, the coefficient of correlation, the variance inflation factor and the condition number. The results obtained are illustrated with two numerical examples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_06171 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Generalized Ridge Regression: Applications to Nonorthogonal Linear Regression Models Gómez, Román Salmerón García, Catalina García Reina, Guillermo Hortal Methodology 62J05 This paper analyzes the possibilities of using the generalized ridge regression to mitigate multicollinearity in a multiple linear regression model. For this purpose, we obtain the expressions for the estimated variance, the coefficient of variation, the coefficient of correlation, the variance inflation factor and the condition number. The results obtained are illustrated with two numerical examples. |
| title | Generalized Ridge Regression: Applications to Nonorthogonal Linear Regression Models |
| topic | Methodology 62J05 |
| url | https://arxiv.org/abs/2504.06171 |