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

J. K. Baksalary; R. Kala

Mathematica Applicanda (1978)

  • Volume: 6, Issue: 12
  • ISSN: 1730-2668

Abstract

top
In the general linear model Ey=Xξ, the vector Cξ is estimable whenever there exists a matrix L such that ELy=Cξ. Several characterizations of estimability are presented. The haracterizations concern matrix and rank equalities based on X and XX′.  Moreover, usefulness of such characterizations is discussed from a computational point of view. For new results on this subject see a paper by I. S. Alalouf and G. P. H. Styan

How to cite

top

J. K. Baksalary, and R. Kala. "Estimability of linear parametric functions in a one-dimensional linear model." Mathematica Applicanda 6.12 (1978): null. <http://eudml.org/doc/292654>.

@article{J1978,
abstract = {In the general linear model Ey=Xξ, the vector Cξ is estimable whenever there exists a matrix L such that ELy=Cξ. Several characterizations of estimability are presented. The haracterizations concern matrix and rank equalities based on X and XX′.  Moreover, usefulness of such characterizations is discussed from a computational point of view. For new results on this subject see a paper by I. S. Alalouf and G. P. H. Styan},
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},
url = {http://eudml.org/doc/292654},
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
JO - Mathematica Applicanda
PY - 1978
VL - 6
IS - 12
SP - null
AB - In the general linear model Ey=Xξ, the vector Cξ is estimable whenever there exists a matrix L such that ELy=Cξ. Several characterizations of estimability are presented. The haracterizations concern matrix and rank equalities based on X and XX′.  Moreover, usefulness of such characterizations is discussed from a computational point of view. For new results on this subject see a paper by I. S. Alalouf and G. P. H. Styan
LA - eng
KW - Linear regression
UR - http://eudml.org/doc/292654
ER -

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.