r-k CLASS ESTIMATION IN REGRESSION MODEL
WITH CONCOMITANT VARIABLES

MASAYUKI JIMICHI 1 AND NOBUO INAGAKI 2

1 School of Business Administration, Kwansei Gakuin University,
1-155, Uegaharaichiban-cho, Nishinomiya, Hyogo 662, Japan

2 Department of Mathematical Science, Faculty of Engineering Science, Osaka University,
Machikaneyama-cho, Toyonaka, Osaka 560, Japan

(Received August 8, 1994; revised April 25, 1995)

Abstract.    We treat with the r-k class estimation in a regression model, which includes the ordinary least squares estimator, the ordinary ridge regression estimator and the principal component regression estimator as special cases of the r-k class estimator. Many papers compared total mean square error of these estimators. Sarkar (1989, Ann. Inst. Statist. Math., 41, 717-724) asserts that the results of this comparison are still valid in a misspecified linear model. We point out some confusions of Sarkar and show additional conditions under which his assertion holds.

Key words and phrases:    Concomitant variables, multicollinearity, ordinary least squares estimator, ordinary ridge regression estimator, principal component regression estimator, r-k class estimator.

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