|
[1] J. Durbin, A note on regression when there is extraneous information about one of the coefficients, J. Amer. Statist. Assoc. 48 (1953), 799-808.
[2] C. R. Rao and H. Toutenburg, Linear Models: Least Squares and Alternatives, 2nd ed., Springer, New York, 1999.
[3] T. Teräsvirta, Superiority comparisons of homogeneous linear estimators, Comm. Statist. Part A Theory Methods 11 (1982), 1595-1601.
[4] T. Teräsvirta, Superiority comparisons of heterogeneous linear estimators, Comm. Statist. Part A Theory Methods 15 (1986), 1319-1336.
[5] H. Theil and A. S. Goldberger, On pure and mixed estimation in econometrics, International Econometric Review 2 (1961), 65-78.
[6] C. Toro-Vizcarrondo and T. D. Wallace, A test of the mean square error criterion for restrictions in linear regression, J. Amer. Statist. Assoc. 63(322) (1968), 558-572.
[7] H. Toutenburg, Prior Information in Linear Models, Wiley, New York, 1982.
[8] G. Trenkler, Mean square error matrix comparisons of estimators in linear regression, Comm. Statist. Part A Theory Methods 14 (1985), 2495-2509.
[9] G. Trenkler and H. Toutenburg, Mean square error matrix comparisons between biased estimators - an overview of recent results, Statistical Papers 31 (1990), 165-179.
[10] T. D. Wallace and C. Toro-Vizcarrondo, Tables for the mean square error test for exact linear restrictions in regression, J. Amer. Statist. Assoc. 64(328) (1969), 1649-1663. |