Publicación: A NON STOCHASTIC RIDGE REGRESSION ESTIMATOR AND COMPARISON WITH THE JAMES-STEIN ESTIMATOR
Fecha
2016
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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Resumen
THIS ARTICLE PRESENTS A NON-STOCHASTIC VERSION OF THE GENERALIZED RIDGE REGRESSION ESTIMATOR THAT ARISES FROM A DISCUSSION OF THE PROPERTIES OF A GENERALIZED RIDGE REGRESSION ESTIMATOR WHOSE SHRINKAGE PARAMETERS ARE FOUND TO BE CLOSE TO THEIR UPPER BOUNDS. THE RESULTING ESTIMATOR TAKES THE FORM OF A SHRINKAGE ESTIMATOR THAT IS SUPERIOR TO BOTH THE ORDINARY LEAST SQUARES ESTIMATOR AND THE JAMES-STEIN ESTIMATOR UNDER CERTAIN CONDITIONS. A NUMERICAL STUDY IS PROVIDED TO INVESTIGATE THE RANGE OF SIGNAL TO NOISE RATIO UNDER WHICH THE NEW ESTIMATOR DOMINATES THE JAMES-STEIN ESTIMATOR WITH RESPECT TO THE PREDICTION MEAN SQUARE ERROR.
