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Weighted Ridge Regression: Combining Ridge and Robust Regression Methods

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  • Paul W. Holland

Abstract

This paper gives the formulas for and derivation of ridge regression methods when there are weights associated with each observation. A Bayesian motivation is used and various choices of k are discussed. A suggestion is made as to how to combine ridge regression with robust regression methods.

Suggested Citation

  • Paul W. Holland, 1973. "Weighted Ridge Regression: Combining Ridge and Robust Regression Methods," NBER Working Papers 0011, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:0011
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    Cited by:

    1. David C. Hoaglin, 1973. "Monte Carlo Techniques in Studying Robust Estimators," NBER Working Papers 0016, National Bureau of Economic Research, Inc.
    2. G.S. Maddala, 1974. "Ridge Estimators for Distributed Lag Models," NBER Working Papers 0069, National Bureau of Economic Research, Inc.
    3. Asuman Turkmen & Omer Ozturk, 2014. "Rank-based ridge estimation in multiple linear regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 737-754, December.

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