Robust statistics: theory and methods with R

Robust Statistics: Theory and Methods (W

📁 Robust Statistics: Theory and Methods (With R)

✍ Ricardo A. Maronna, R. Douglas Martin, Victor J. Yohai, Matias Salibian-Barrera 📂 Library 📅 2018 🏛 Wiley-Blackwell 🌐 English

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with devi

Robust Statistics: Theory and Methods (w

📁 Robust Statistics: Theory and Methods (with R), 2nd edition

✍ Ricardo A. Maronna, R. Douglas Martin 📂 Library 📅 2019 🏛 John Wiley & Sons 🌐 English

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from stand

Robust Statistical Methods with R

📁 Robust Statistical Methods with R

✍ Jana Jureckova, Jan Picek 📂 Library 📅 2005 🏛 Chapman and Hall/CRC 🌐 English

Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robu

Robust Statistical Methods With R

📁 Robust Statistical Methods With R

✍ Jana Jurečková, Jan Picek, Martin Schindler 📂 Library 📅 2019 🏛 CRC Press/Taylor & Francis Group 🌐 English

The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model cont

Robust statistical methods with R

📁 Robust statistical methods with R

✍ Jurečková, Jana; Picek, Jan; Schindler, Martin 📂 Library 📅 2019 🏛 CRC Press 🌐 English

The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model cont

Robust Statistical Methods with R

📁 Robust Statistical Methods with R

✍ Jureckova J., Picek J. 📂 Library 📅 2005 🌐 English

Developed at Charles University in Prague, this graduate textbook explains the mathematical theory behind maximum likelihood estimators (M-estimators), L-estimators based on order statistics, R-estimators based on the ranks of their residuals, the multivariate location model, and some goodness-of-fi

Robust statistics: theory and methods with R

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