Results 11 to 20 of about 68 (66)

Integration and backfitting methods in additive models-finite sample properties and comparison [PDF]

, 1998
Additive models, curse of dimensionality, dimensionality reduction, model choice, nonparametric regression, 62G07, 62G20, 62G35,
Stefan Sperlich, Hardle, W, Hardle, Wolfgang, Linton, Oliver, Sperlich, Stefan Andréas, Oliver Linton, Sperlich, Stefan, Linton, Oliver B., Wolfgang Härdle, Haerdle, Wolfgang, Sperlich, S   +10 more
core   +1 more source

Influence function and efficiency of the minimum covariance determinant scatter matrix estimator [PDF]

, 1999
peer reviewedThe minimum covariance determinant (MCD) scatter estimator is a highly robust estimator for the dispersion matrix of a multivariate, elliptically symmetric distribution. It is relatively fast to compute and intuitively appealing.
Croux, Christophe, Croux, C., Haesbroeck, Gentiane, Haesbroeck, G.   +3 more
core   +1 more source

Robust kernel principal component analysis and classification

, 2010
Principal component analysis, Kernel methods, Classification, Robustness, 62H30, 62G35,
Michiel Debruyne, Tim Verdonck, Debruyne, Michiel, Verdonck, Tim   +3 more
core   +1 more source

Detection of multivariate outliers in business survey data with incomplete information

, 2010
Multivariate outlier detection, Robust statistics, Missing values, 62G35, 62D05, 62H99,
Valentin Todorov, Filzmoser, Peter, Matthias Templ, Todorov, Valentin, Templ, Matthias, Peter Filzmoser   +5 more
core   +1 more source

Uniform convergence of adversarially robust classifiers

European Journal of Applied Mathematics
In recent years, there has been significant interest in the effect of different types of adversarial perturbations in data classification problems. Many of these models incorporate the adversarial power, which is an important parameter with an associated
Rachel Morris, Ryan Murray
doaj   +1 more source

On the existence of solutions to adversarial training in multiclass classification

European Journal of Applied Mathematics
Adversarial training is a min-max optimization problem that is designed to construct robust classifiers against adversarial perturbations of data. We study three models of adversarial training in the multiclass agnostic-classifier setting.
Nicolás García Trillos, Matt Jacobs, Jakwang Kim   +2 more
doaj   +1 more source

Estimation for spatial semi-functional partial linear regression model with missing response at random

Demonstratio Mathematica
The aim of this article is to study a semi-functional partial linear regression model (SFPLR) for spatial data with responses missing at random (MAR).
Benchikh Tawfik, Almanjahie Ibrahim M., Fetitah Omar, Attouch Mohammed Kadi   +3 more
doaj   +1 more source

Influence Functions of the Spearman and Kendall Correlation Measures [PDF]

, 2010
Mathematics Subject Classification (2000) 62G35 ...
Croux, C., Dehon, C.
core  

Fast and robust estimation of the multivariate errors in variables model

, 2009
Errors in variables, Multivariate statistics, Principal components, Projection-pursuit, Robustness, 62G35, 62H99,
Croux, Christophe, Anne Ruiz-Gazen, Ruiz-Gazen, A., Fekri, M., Ruiz-Gazen, Anne, Christophe Croux, Mohammed Fekri   +6 more
core   +1 more source

The cost of not knowing the radius

, 2008
Symmetric location and contamination, Infinitesimal asymmetric neighborhoods, Total variation, contamination, Asymptotically linear estimators, Influence curves, Maximum asymptotic variance and mean square error, Relative risk, Inefficiency, Least ...
Peter Ruckdeschel, Ruckdeschel, Peter, Rieder, Helmut, Matthias Kohl, Kohl, Matthias, Helmut Rieder   +5 more
core   +1 more source