Estimability of linear parametric functions in a one-dimensional linear model with restrictions

J. K. Baksalary, and R. Kala. "Estimability of linear parametric functions in a one-dimensional linear model with restrictions." Mathematica Applicanda 6.12 (1978): null. <http://eudml.org/doc/293146>.

@article{J1978,
abstract = {The problem of estimability of the vector Cξ in the general linear model Ey=Xξ is discussed. It is assumed that the vector of parameters ξ is a linear manifold Ω given by Rξ=s, where the matrix R and the vector s are known. The vector Cξ is estimable if there exist matrices L and M such that ELy+Ms=Cξ for all ξ in Ω. Using the results of a paper by the authors [62046 above], necessary and sufficient conditions for estimability are presented with short and elegant proofs.},
author = {J. K. Baksalary, R. Kala},
journal = {Mathematica Applicanda},
keywords = {Linear regression},
language = {eng},
number = {12},
pages = {null},
title = {Estimability of linear parametric functions in a one-dimensional linear model with restrictions},
url = {http://eudml.org/doc/293146},
volume = {6},
year = {1978},
}

TY - JOUR
AU - J. K. Baksalary
AU - R. Kala
TI - Estimability of linear parametric functions in a one-dimensional linear model with restrictions
JO - Mathematica Applicanda
PY - 1978
VL - 6
IS - 12
SP - null
AB - The problem of estimability of the vector Cξ in the general linear model Ey=Xξ is discussed. It is assumed that the vector of parameters ξ is a linear manifold Ω given by Rξ=s, where the matrix R and the vector s are known. The vector Cξ is estimable if there exist matrices L and M such that ELy+Ms=Cξ for all ξ in Ω. Using the results of a paper by the authors [62046 above], necessary and sufficient conditions for estimability are presented with short and elegant proofs.
LA - eng
KW - Linear regression
UR - http://eudml.org/doc/293146
ER -