A restricted r{-}k$$ r - k class estimator in the mixed regression model with autocorrelated disturbances (original) (raw)
In this paper, a new estimator called the restricted r-k class estimator, is introduced when the linear restrictions binding the regression coefficients are stochastic in nature, by combining the ordinary ridge regression estimator and principal component regression estimator for a regression model suffering from the problem of multicollinearity. The performance of the proposed r-k class estimator in the mixed regression model is compared with that of the mixed regression estimator and the stochastic ridge regression estimator in terms of the mean square error matrix criterion. Tests for verifying the conditions of dominance of the proposed estimator over the two others are also proposed. Furthermore, a Monte Carlo study and a numerical evaluation are carried out to study the performance of the tests involving conditions of superiority of the proposed estimator over the other two.
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