Abstract
In this paper we consider a linear regression model with omitted relevant regressors and multivariatet error terms. The explicit formula for the Pitman nearness criterion of the Stein-rule (SR) estimator relative to the ordinary least squares (OLS) estimator is derived. It is shown numerically that the dominance of the SR estimator over the OLS estimator under the Pitman nearness criterion can be extended to the case of the multivariatet error distribution when the specification error is not severe. It is also shown that the dominance of the SR estimator over the OLS estimator cannot be extended to the case of the multivariatet error distribution when the specification error is severe.
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This research is partially supported by the Grants-in-Aid for 21st Century COE program.
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Namba, A., Ohtani, K. Risk comparison of the Stein-rule estimator in a linear regression model with omitted relevant regressors and multivariatet errors under the Pitman nearness criterion. Statistical Papers 48, 151–162 (2007). https://doi.org/10.1007/s00362-006-0321-z
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DOI: https://doi.org/10.1007/s00362-006-0321-z