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Robust Statistics: Theory and Methods (with R)

Second edition., 2019

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Robust Estimates of Location and Dispersion for High-Dimensional Datasets

Technometrics, 2002-11, Vol.44 (4), p.307-317

2002

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Robust Ridge Regression for High-Dimensional Data

Technometrics, 2011-02, Vol.53 (1), p.44-53

Maronna, Ricardo A.

2011

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Robust functional principal components for irregularly spaced longitudinal data

Statistical papers (Berlin, Germany), 2021-08, Vol.62 (4), p.1563-1582

Maronna, Ricardo A.

2021

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Robust and efficient estimation of multivariate scatter and location

Computational statistics & data analysis, 2017-05, Vol.109, p.64-75

2017

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Robust Estimators for Data Reconciliation

Industrial & engineering chemistry research, 2015-05, Vol.54 (18), p.5096-5105

2015

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Robust Estimation of Nonredundant Measurements and Equivalent Sets of Observations

Industrial & engineering chemistry research, 2019-10, Vol.58 (42), p.19551-19561

2019

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Classification of Systematic Measurement Errors within the Framework of Robust Data Reconciliation

Industrial & engineering chemistry research, 2017-08, Vol.56 (34), p.9617-9628

2017

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Optimal robust estimators for families of distributions on the integers

Statistical papers (Berlin, Germany), 2021-10, Vol.62 (5), p.2269-2281

2021

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Comments on: Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination

Test (Madrid, Spain), 2015-09, Vol.24 (3), p.471-472

Maronna, Ricardo A.

2015

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High finite-sample efficiency and robustness based on distance-constrained maximum likelihood

Computational statistics & data analysis, 2015-03, Vol.83, p.262-274

2015

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Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini

Statistical methods & applications, 2018-12, Vol.27 (4), p.603-604

2018

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Dynamic System State Estimation and Outlier Detection Using Robust Data Reconciliation

Chemical engineering transactions, 2019-05, Vol.74

2019

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Correcting MM estimates for “fat” data sets

Computational statistics & data analysis, 2010-12, Vol.54 (12), p.3168-3173

2010

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Estimates of MM type for the multivariate linear model

Journal of multivariate analysis, 2011-10, Vol.102 (9), p.1280-1292

2011

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Robust nonlinear principal components

Statistics and computing, 2015-03, Vol.25 (2), p.439-448

2015

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A robust methodology for the sensor fault detection and classification of systematic observation errors

Computer Aided Chemical Engineering, 2017-01, Vol.40, p.1525-1530

2017

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Continuity and differentiability of regression M functionals

Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2012-11, Vol.18 (4), p.1284-1309

2012

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Robust Low-Rank Approximation of Data Matrices With Elementwise Contamination

Technometrics, 2008-08, Vol.50 (3), p.295-304

2008

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Robust functional linear regression based on splines

Computational statistics & data analysis, 2013-09, Vol.65, p.46-55

2013

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The Behavior of the Stahel-Donoho Robust Multivariate Estimator

Journal of the American Statistical Association, 1995-03, Vol.90 (429), p.330-341

1995

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Robust regression quantiles

Journal of statistical planning and inference, 2004-05, Vol.122 (1), p.187-202

2004

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Robust Statistics, 2nd Edition

2019

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Relationships between maximum depth and projection regression estimates

Journal of statistical planning and inference, 2002-07, Vol.105 (2), p.363-375

2002

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Correcting MM estimates for fat data sets : Variable selection and robust procedures

Computational statistics & data analysis, 2010, Vol.54 (12), p.3168-3173

2010

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Robust Statistics: Theory and Methods (with R)

Robust Estimates of Location and Dispersion for High-Dimensional Datasets

Robust Ridge Regression for High-Dimensional Data

Robust functional principal components for irregularly spaced longitudinal data

Robust and efficient estimation of multivariate scatter and location

Robust Estimators for Data Reconciliation

Robust Estimation of Nonredundant Measurements and Equivalent Sets of Observations

Classification of Systematic Measurement Errors within the Framework of Robust Data Reconciliation

Optimal robust estimators for families of distributions on the integers

Comments on: Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination

High finite-sample efficiency and robustness based on distance-constrained maximum likelihood

Discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample” by Andrea Cerioli, Marco Riani, Anthony C. Atkinson and Aldo Corbellini

Dynamic System State Estimation and Outlier Detection Using Robust Data Reconciliation

Correcting MM estimates for “fat” data sets

Estimates of MM type for the multivariate linear model

Robust nonlinear principal components

A robust methodology for the sensor fault detection and classification of systematic observation errors

Continuity and differentiability of regression M functionals

Robust Low-Rank Approximation of Data Matrices With Elementwise Contamination

Robust functional linear regression based on splines

The Behavior of the Stahel-Donoho Robust Multivariate Estimator

Robust regression quantiles

Robust Statistics, 2nd Edition

Relationships between maximum depth and projection regression estimates

Correcting MM estimates for fat data sets : Variable selection and robust procedures

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