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Partial Factor Modeling: Predictor-Dependent Shrinkage for Linear Regression
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AI
DOI：10.1080/01621459.2013.779843.png)
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We develop a modified Gaussian factor model for the purpose of inducing predictor-dependent shrinkage for linear regression. The new model predicts well across a wide range of covariance structures, on real and simulated data. Furthermore, the new model facilitates variable selection in the case of correlated predictor variables, which often stymies other methods.
Keyword:
g Prior
Prediction
Shrinkage estimators
Variable selection
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J
IF:
3
论文数:
5.2K
被引数:
4.8W
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