| Autor: |
Akbar Irandoukht |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Journal of Statistical Theory and Applications (JSTA), Vol 20, Iss 2 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2214-1766 |
| DOI: |
10.2991/jsta.d.210322.001 |
| Popis: |
The presence of the multicollinearity problem in the predictor data causes the variance of the ordinary linear regression coefficients to be increased so that the prediction power of the model not to be satisfied and sometimes unacceptable results be predicted. The ridge regression has been proposed as an efficient method to combat multicollinearity problem long ago. In application of ridge regression the researcher uses the ridge trace and selects a value of ridge parameter in such a manner that he thinks the regression coefficients have stabilized; this leads the ridge regression to be subjective technique. The purpose of this paper is the conversion of the ridge regression method from a qualitative method to a quantitative one meanwhile to present a method to find the optimum ridge regression parameter which maximizes the R-squared of prediction. We examined four well-known case studies on this regard. Significant improvements at all of the cases demonstrated the validity of our proposed method. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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