The Annals of Statistics

Linear Transformations Preserving Best Linear Unbiased Estimators in a General Gauss-Markoff Model

J. K. Baksalary and R. Kala

Full-text: Open access

Abstract

Under a general Gauss-Markoff model $\{\mathbf{y}, \mathbf{X,\beta, V}\}$, a necessary and sufficient condition is established for a linear transformation, $\mathbf{F}$, of the observable random vector $\mathbf{y}$ to have the property that there exists a linear function of $\mathscr{Fy}$ which is a BLUE of $\mathbf{X\beta}$. A method for deriving a required BLUE from the transformed model $\{\mathbf{Fy, FX\beta, FVF}'\}$ is also indicated.

Article information

Source
Ann. Statist., Volume 9, Number 4 (1981), 913-916.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176345533

Digital Object Identifier
doi:10.1214/aos/1176345533

Mathematical Reviews number (MathSciNet)
MR619297

Zentralblatt MATH identifier
0471.62067

JSTOR
links.jstor.org

Subjects
Primary: 62J05: Linear regression

Keywords
General Gauss-Markoff model best linear unbiased estimator linear transformation

Citation

Baksalary, J. K.; Kala, R. Linear Transformations Preserving Best Linear Unbiased Estimators in a General Gauss-Markoff Model. Ann. Statist. 9 (1981), no. 4, 913--916. doi:10.1214/aos/1176345533. https://projecteuclid.org/euclid.aos/1176345533


Export citation