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Improved variance estimation under sub-space restriction. (English) Zbl 1163.62041

Summary: For the linear regression model \(y = X \beta +\varepsilon\), we assume that for a given positive definite scale matrix \(\varSigma\), the error vector has a multivariate normal distribution and \(\varSigma\) has the inverted Wishart distribution. Under an orthogonal sub-space restriction \(H\beta = h\), we propose restricted unbiased, preliminary test and C. Stein-type [Ann. Inst. Stat. Math. 16, 155–160 (1964; Zbl 0144.41405)] estimators of the variance of the error term, when the scale of the inverse Wishart distribution is assumed to be unknown. We compare the weighted quadratic risks of the underlying estimators and propose dominance pictures for them.

MSC:

62H12 Estimation in multivariate analysis
62J05 Linear regression; mixed models
62F30 Parametric inference under constraints

Citations:

Zbl 0144.41405
Full Text: DOI

References:

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