In this paper we introduce the least-trimmed squares estimator for multivariate regression. We give three equivalent formulations of the estimator and obtain its breakdown point. A fast algorithm for its computation is proposed. We prove Fisher-consistency at the multivariate regression model with elliptically symmetric error distribution and derive the influence function. Simulations investigate the finite-sample efficiency and robustness of the estimator. To increase the efficiency of the estimator, we also consider a one-step reweighted estimator. © 2006 Elsevier Inc. All rights reserved.status: publishe
Abstract. We review Hildreth's algorithm for computing the least squares regression subject to ...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
AbstractIn this paper we introduce the least-trimmed squares estimator for multivariate regression. ...
In this paper we introduce the least trimmed squares estimator for multivariate regression. We give ...
In this paper we introduce the least trimmed squares estimator for multivariate regression. We give ...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
Instead of minimizing the sum of all $n$ squared residuals as the classical least squares (LS) does,...
This article was published in an Elsevier journal. The attached copy is furnished to the author for ...
The vector autoregressive model is very popular for modeling multiple time series. Estimation of its...
summary:From the practical point of view the regression analysis and its Least Squares method is cle...
Abstract. The vector autoregressive model is very popular for modeling multi-ple time series. Estima...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
[[abstract]]The ordinary least squares (OLS) method is popular for analyzing linear regression model...
Abstract. We review Hildreth's algorithm for computing the least squares regression subject to ...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
AbstractIn this paper we introduce the least-trimmed squares estimator for multivariate regression. ...
In this paper we introduce the least trimmed squares estimator for multivariate regression. We give ...
In this paper we introduce the least trimmed squares estimator for multivariate regression. We give ...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
Instead of minimizing the sum of all $n$ squared residuals as the classical least squares (LS) does,...
This article was published in an Elsevier journal. The attached copy is furnished to the author for ...
The vector autoregressive model is very popular for modeling multiple time series. Estimation of its...
summary:From the practical point of view the regression analysis and its Least Squares method is cle...
Abstract. The vector autoregressive model is very popular for modeling multi-ple time series. Estima...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
[[abstract]]The ordinary least squares (OLS) method is popular for analyzing linear regression model...
Abstract. We review Hildreth's algorithm for computing the least squares regression subject to ...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...