A Constrained Linear Estimator for Multiple Regression

作者：Davis Stober Clintin P^*; Dana Jason; Budescu David V

来源：Psychometrika, 2010, 75(3): 521-541.

DOI：10.1007/s11336-010-9162-8

• least squares
• inconsistent estimators
• improper linear models
• unit weights
• equal weights
• take the best
• constrained models

"Improper linear models" (see Dawes, Am. Psychol. 34:571-582, 1979), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of "improper" linear models as "proper" statistical models with a single predictor. We derive the upper bound on the mean squared error of this estimator and demonstrate that it has less variance than ordinary least squares estimates. We examine common choices of the weighting vector used in the literature, e.g., single variable heuristics and equal weighting, and illustrate their performance in various test cases.

• 出版日期2010-9