Radhakrishna Rao, C. (1979) Estimation of parameters in the singular Gauss-Markoff model Communications in Statistics - Theory and Methods, 8 (14). pp. 1353-1358. ISSN 0361-0926
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Official URL: http://www.tandfonline.com/doi/abs/10.1080/0361092...
Related URL: http://dx.doi.org/10.1080/03610927908827835
Abstract
Consider the Gauss-Markoff model (Y, Xβ, σ2V) in the usual notation (Rao, 1973a, p. 294). If V is singular, there exists a matrix N such that N'Y has zero covariance. The minimum variance unbiased estimator of an estimable parametric function p'β is obtained in the wider class of (non-linear) unbiased estimators of the form f(N'Y) + Y'g(N'Y) where f is a scalar and g is a vector function.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Taylor and Francis Group. |
| Keywords: | Gauss-Markoff Model; Unbiased Estimation; Singular Dispersion Matrix |
| ID Code: | 71849 |
| Deposited On: | 28 Nov 2011 04:10 |
| Last Modified: | 28 Nov 2011 04:10 |
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