The consistency and the asymptotic normality of the least weighted squares is proved and its asymptotic representation derived. Although the proof includes rather large amount of technicalities, it is not difficult to follow. The technique as follows from the analogy with the least trimmed squares will allow to study also the sensitivity of estimator to the influential points. The results and the properties of the estimator are discussed in the Conclusions at the end of paper.Robust regression, the least weighted squares, consistency, asymptotic normality, asymptotic representation
We consider a heteroscedastic linear regression model with replication. To estimate the variances, o...
AbstractLeast squares estimation of the parameters of a single input-single output linear autonomous...
AbstractThe strong consistency of least squares estimates in multiple regression models is establish...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
summary:A robust version of the Ordinary Least Squares accommodating the idea of weighting the order...
summary:$\sqrt{n}$-consistency of the least trimmed squares estimator is proved under general condit...
summary:The present paper deals with least weighted squares estimator which is a robust estimator an...
summary:Asymptotic normality of the least trimmed squares estimator is proved under general conditio...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...
This thesis deals with asymptotic properties of least squares estimators of regression coefficients ...
AbstractThe paper uses empirical process techniques to study the asymptotics of the least-squares es...
This paper investigates the asymptotic properties of least squares estimates of Hammerstein-Wiener ...
The paper uses empirical process techniques to study the asymptotics of the least-squares estimator ...
AbstractThis paper establishes several almost sure asymptotic properties of general autoregressive p...
We consider a heteroscedastic linear regression model with replication. To estimate the variances, o...
AbstractLeast squares estimation of the parameters of a single input-single output linear autonomous...
AbstractThe strong consistency of least squares estimates in multiple regression models is establish...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
summary:A robust version of the Ordinary Least Squares accommodating the idea of weighting the order...
summary:$\sqrt{n}$-consistency of the least trimmed squares estimator is proved under general condit...
summary:The present paper deals with least weighted squares estimator which is a robust estimator an...
summary:Asymptotic normality of the least trimmed squares estimator is proved under general conditio...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...
This thesis deals with asymptotic properties of least squares estimators of regression coefficients ...
AbstractThe paper uses empirical process techniques to study the asymptotics of the least-squares es...
This paper investigates the asymptotic properties of least squares estimates of Hammerstein-Wiener ...
The paper uses empirical process techniques to study the asymptotics of the least-squares estimator ...
AbstractThis paper establishes several almost sure asymptotic properties of general autoregressive p...
We consider a heteroscedastic linear regression model with replication. To estimate the variances, o...
AbstractLeast squares estimation of the parameters of a single input-single output linear autonomous...
AbstractThe strong consistency of least squares estimates in multiple regression models is establish...