AbstractThis paper surveys the problem of estimating a linear relationship between variables which are observed with error. These are either fixed variables (functional relationship) or random variables (structural relationship). After considering various conditions for identifiability, estimation methods are surveyed in various cases when additional information is available, including Wald's method, the use of instrumental variates, and the case of more than two variables. The paper concludes with a list of unsolved problems
This article deals with multiple linear functional relationships models. Two robust estimations proc...
In this paper, we propose a robust parameter estimation method for the linear functional relationshi...
Thesis (Ph.D.)--University of Washington, 2018We are interested in the extent to which, possibly cau...
AbstractThis paper surveys the problem of estimating a linear relationship between variables which a...
AbstractThis paper deals with maximum likelihood estimation of linear or nonlinear functional relati...
by Chung Sai Ho.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical ref...
An estimation procedure based on estimating equations is presented for the parameters in a multivari...
Given a sufficient number of instrumental variables significantly correlated with the investigationa...
Abstract: Given a sufficient number of instrumental variables significantly correlated with the inve...
AbstractMany authors have discussed maximum likelihood estimation in the simple linear functional re...
This thesis deals with a linear functional relationship model in which the unobserved true values sa...
A maximum likelihood solution is obtained for the simple linear structural relation model where the ...
AbstractThis paper considers the Maximum Likelihood (ML) estimation of the five parameters of a line...
Maximum likelihood estimation of parameters in linear structural relationships under normality assum...
. A general linear model can be written as Y = XB 0 + U , where Y is an N \Theta p matrix of obser...
This article deals with multiple linear functional relationships models. Two robust estimations proc...
In this paper, we propose a robust parameter estimation method for the linear functional relationshi...
Thesis (Ph.D.)--University of Washington, 2018We are interested in the extent to which, possibly cau...
AbstractThis paper surveys the problem of estimating a linear relationship between variables which a...
AbstractThis paper deals with maximum likelihood estimation of linear or nonlinear functional relati...
by Chung Sai Ho.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical ref...
An estimation procedure based on estimating equations is presented for the parameters in a multivari...
Given a sufficient number of instrumental variables significantly correlated with the investigationa...
Abstract: Given a sufficient number of instrumental variables significantly correlated with the inve...
AbstractMany authors have discussed maximum likelihood estimation in the simple linear functional re...
This thesis deals with a linear functional relationship model in which the unobserved true values sa...
A maximum likelihood solution is obtained for the simple linear structural relation model where the ...
AbstractThis paper considers the Maximum Likelihood (ML) estimation of the five parameters of a line...
Maximum likelihood estimation of parameters in linear structural relationships under normality assum...
. A general linear model can be written as Y = XB 0 + U , where Y is an N \Theta p matrix of obser...
This article deals with multiple linear functional relationships models. Two robust estimations proc...
In this paper, we propose a robust parameter estimation method for the linear functional relationshi...
Thesis (Ph.D.)--University of Washington, 2018We are interested in the extent to which, possibly cau...