AbstractGlobal depth, tangent depth and simplicial depths for classical and orthogonal regression are compared in examples, and properties that are useful for calculations are derived. The robustness of the maximum simplicial depth estimates is shown in examples. Algorithms for the calculation of depths for orthogonal regression are proposed, and tests for multiple regression are transferred to orthogonal regression. These tests are distribution free in the case of bivariate observations. For a particular test problem, the powers of tests that are based on simplicial depth and tangent depth are compared by simulations
Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance f...
The location depth (Tukey 1975) of a point relative to a p-dimensional data set Z of size n is defi...
Regression analysis is a statistical technique for investigating and modeling the relationship betwe...
AbstractGlobal depth, tangent depth and simplicial depths for classical and orthogonal regression ar...
AbstractA general approach for developing distribution free tests for general linear models based on...
In this paper we present the maximum simplicial depth estimator and compare it to the ordinary least...
ABSTRACT. In this paper we present the maximum simplicial depth estimator and compare it to the ordi...
In this paper we present the maximum simplicial depth estimator and compare it to the ordinary least...
A fast algorithm for calculating the simplicial depth of a single parameter vector of a polynomial r...
We simplify simplicial depth for regression and autoregressive growth processes in two directions. ...
AbstractA general depth measure, based on the use of one-dimensional linear continuous projections, ...
Mizera’s previous work [13] introduced tangent depth, a powerful method for defining robust statisti...
The extension of simplicial depth to robust regression, the so-called simplicial regression depth, ...
While the halfspace depth has gained more and more popularity in the recent years as a robust estima...
A new multivariate concept of quantile, based on a directional version of Koenker and Bassett s trad...
Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance f...
The location depth (Tukey 1975) of a point relative to a p-dimensional data set Z of size n is defi...
Regression analysis is a statistical technique for investigating and modeling the relationship betwe...
AbstractGlobal depth, tangent depth and simplicial depths for classical and orthogonal regression ar...
AbstractA general approach for developing distribution free tests for general linear models based on...
In this paper we present the maximum simplicial depth estimator and compare it to the ordinary least...
ABSTRACT. In this paper we present the maximum simplicial depth estimator and compare it to the ordi...
In this paper we present the maximum simplicial depth estimator and compare it to the ordinary least...
A fast algorithm for calculating the simplicial depth of a single parameter vector of a polynomial r...
We simplify simplicial depth for regression and autoregressive growth processes in two directions. ...
AbstractA general depth measure, based on the use of one-dimensional linear continuous projections, ...
Mizera’s previous work [13] introduced tangent depth, a powerful method for defining robust statisti...
The extension of simplicial depth to robust regression, the so-called simplicial regression depth, ...
While the halfspace depth has gained more and more popularity in the recent years as a robust estima...
A new multivariate concept of quantile, based on a directional version of Koenker and Bassett s trad...
Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance f...
The location depth (Tukey 1975) of a point relative to a p-dimensional data set Z of size n is defi...
Regression analysis is a statistical technique for investigating and modeling the relationship betwe...