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Home Features of DataLab Mathematical/Statistical Analysis Modelling Multiple Regression Ridge Regression Create an RR model |
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See also: MLR - Multiple Linear Regression, Apply an MLR Model, Apply an RR Model
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Create a Ridge Regression Model
Ridge regression is a method to cope with parameter instabilities when some of the descriptor variables are highly correlated. See the statistical background for more information.
The command Math/Multiple Regression/Ridge Regression... (toolbar button
). After that the most important diagrams for checking the regression are displayed in the diagnostic window tabs. These diagrams contain the plot of the estimated vs. the actual target values, the distribution of the residuals, and the residuals plotted against an arbitrary independent variable or against the object number. The details on the results can be viewed in the "Details" tab. Further, the ridge trace and the associated levels of significance of the model parameters are displayed in the "Ridge Trace" tab, and the cross validation for different levels of the ridge parameter Lambda can be performed on the "Cross Validation" tab.
The ridge trace (see figure above) shows the estimated parameters over the value of Lambda. It offers a second tab showing the signficance of the estimated parameters over Lambda (figure below). The 5% level of significance is displayed as a gray dotted line. Significant parameters are below this level.
You can store the model on the disk (
In order to make the variable selection easier the detection of multicollinearities (
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