"IMPROVED RIDGE ESTIMATOR IN LINEAR REGRESSION . . ." by Ashok Vithoba Dorugade
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Abstract

This paper introduces a new estimator, of ridge parameter k for ridge regression and then evaluated by Monte Carlo simulation. We examine the performance of the proposed estimators compared with other well-known estimators for the model with heteroscedastics and/or correlated errors, outlier observations, non-normal errors and suffer from the problem of multicollinearity. It is shown that proposed estimators have a smaller MSE than the ordinary least squared estimator (LS), Hoerl and Kennard (1970) estimator (RR), jackknifed modified ridge (JMR) estimator, and Jackknifed Ridge M‑estimator (JRM).

DOI

10.22237/jmasm/1478002860

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