Add to ORKGRecently the concept of regression depth has been introduced [J. Am. Stat. Assoc. 94 (1999) 388]. The deepest regression (DR) is a method for linear regression which is defined as the fit with the best depth relative to the data. In this paper we explain the properties of the DR and give some applications of DR in analytical chemistry which involve regression through the origin, polynomial regression, the Michaelis-Menten model, and censored responses. © 2001 Elsevier Science B.V. All rights reserved.status: publishe
This article describes the general modus operandi of model-free Multivariate Curve Resolution iterat...
Deep learning gained a lot of traction in the machine learning community. The performance of these m...
Sparse partial robust M regression is introduced as a new regression method. It is the first dimensio...
Recently the concept of regression depth has been introduced [J. Am. Stat. Assoc. 94 (1999) 388]. Th...
Recently the concept of regression depth has been introduced [1]. The deepest regression (DR) is a m...
Deepest regression (DR) is a method for linear regression introduced by P. J. Rousseeuw and M. Huber...
AbstractDeepest regression (DR) is a method for linear regression introduced by P. J. Rousseeuw and ...
In this paper we investigate the robustness properties of the deepest regression, a method for linea...
In this paper we investigate the robustness properties of the deepest regression, a method for linea...
AbstractIn this paper we investigate the robustness properties of the deepest regression, a method f...
Chemometrics is a chemical discipline in which mathematical and statistical techniques are applied t...
While the halfspace depth has gained more and more popularity in the recent years as a robust estima...
The deepest regression method is such a method of estimation of regression parameters that the maxi...
this paper. Procedures built by PolyAnalyst are treated as regression models which are nonlinear in ...
summary:Data depth is an important concept of nonparametric approach to multivariate data analysis. ...
This article describes the general modus operandi of model-free Multivariate Curve Resolution iterat...
Deep learning gained a lot of traction in the machine learning community. The performance of these m...
Sparse partial robust M regression is introduced as a new regression method. It is the first dimensio...
Recently the concept of regression depth has been introduced [J. Am. Stat. Assoc. 94 (1999) 388]. Th...
Recently the concept of regression depth has been introduced [1]. The deepest regression (DR) is a m...
Deepest regression (DR) is a method for linear regression introduced by P. J. Rousseeuw and M. Huber...
AbstractDeepest regression (DR) is a method for linear regression introduced by P. J. Rousseeuw and ...
In this paper we investigate the robustness properties of the deepest regression, a method for linea...
In this paper we investigate the robustness properties of the deepest regression, a method for linea...
AbstractIn this paper we investigate the robustness properties of the deepest regression, a method f...
Chemometrics is a chemical discipline in which mathematical and statistical techniques are applied t...
While the halfspace depth has gained more and more popularity in the recent years as a robust estima...
The deepest regression method is such a method of estimation of regression parameters that the maxi...
this paper. Procedures built by PolyAnalyst are treated as regression models which are nonlinear in ...
summary:Data depth is an important concept of nonparametric approach to multivariate data analysis. ...
This article describes the general modus operandi of model-free Multivariate Curve Resolution iterat...
Deep learning gained a lot of traction in the machine learning community. The performance of these m...
Sparse partial robust M regression is introduced as a new regression method. It is the first dimensio...