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Employing Ridge Regression Technique in Prediction | ||
| IRAQI JOURNAL OF STATISTICAL SCIENCES | ||
| Article 10, Volume 12, Issue 2, 2012, Pages 121-135 PDF (0 K) | ||
| DOI: 10.33899/iqjoss.2012.067722 | ||
| Abstract | ||
| This paper is concerned with fitting some black box models. Some of them are, the outputs error model which contains the autoregressive and autoregressive moving average with additional inputs(ARX and ARMAX).The best model has been chosen which represents the data about the Temperature which is affected by some predictor variables which they were represented by (Brightness, unlike radiation, and evaporation).The parameters of the best model were estimated by the ridge regression method with and without the existence of prior information around the model parameters. The prediction errors of the model which has been estimated by least square and ridge regression when the prior information about the parameters is available were compared. | ||
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