Add to ORKGConditions are given which ensure the nonexistence of a sequence of strongly consistent M-estimators in a general parameter estimation problem. An example is given of a nonlinear regression model used in software engineering and having the property that every sequence of least squares estimators fails to be strongly consistent. © 1992
AbstractThe strong consistency of least squares estimates in multiple regression models is establish...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
Regression models are routinely used in many applied sciences for describing the relationship betwee...
Conditions are given which ensure the nonexistence of a sequence of strongly consistent M-estimators...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
AbstractThis paper extends the results of Chen and Wu [1] concerning consistency of M-estimators in ...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
This paper presents a solution to an important econometric problem, namely the root n consistent est...
Abstract: We study the asymptotic behavior of M-estimates of regression parameters in multiple linea...
In this paper, we consider the problem of robust M-estimation of parameters of nonlinear signal proc...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
We consider the linear model y<SUB>i</SUB> = x'<SUB>i</SUB>β + e<SUB>i</SUB>, i = 1,...,n, and an es...
Standard consistency proofs of the maximum likelihood estimator rely on the assumption that the obse...
AbstractThe strong consistency of least squares estimates in multiple regression models is establish...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
Regression models are routinely used in many applied sciences for describing the relationship betwee...
Conditions are given which ensure the nonexistence of a sequence of strongly consistent M-estimators...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
AbstractThis paper extends the results of Chen and Wu [1] concerning consistency of M-estimators in ...
Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimat...
This paper presents a solution to an important econometric problem, namely the root n consistent est...
Abstract: We study the asymptotic behavior of M-estimates of regression parameters in multiple linea...
In this paper, we consider the problem of robust M-estimation of parameters of nonlinear signal proc...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
We consider the linear model y<SUB>i</SUB> = x'<SUB>i</SUB>β + e<SUB>i</SUB>, i = 1,...,n, and an es...
Standard consistency proofs of the maximum likelihood estimator rely on the assumption that the obse...
AbstractThe strong consistency of least squares estimates in multiple regression models is establish...
A strongly consistent sequence of estimators of the variance of the disturbance term in a nonlinear ...
Regression models are routinely used in many applied sciences for describing the relationship betwee...