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R Statistics Cookbook

You're reading from   R Statistics Cookbook Over 100 recipes for performing complex statistical operations with R 3.5

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789802566
Length 448 pages
Edition 1st Edition
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Author (1):
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Francisco Juretig Francisco Juretig
Author Profile Icon Francisco Juretig
Francisco Juretig
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Table of Contents (12) Chapters Close

Preface 1. Getting Started with R and Statistics FREE CHAPTER 2. Univariate and Multivariate Tests for Equality of Means 3. Linear Regression 4. Bayesian Regression 5. Nonparametric Methods 6. Robust Methods 7. Time Series Analysis 8. Mixed Effects Models 9. Predictive Models Using the Caret Package 10. Bayesian Networks and Hidden Markov Models 11. Other Books You May Enjoy

Robust linear regression

When doing linear regression, we have seen that our estimates can change dramatically in the presence of influential points. This is usually problematic when dealing with noisy datasets. R exposes the rlm function, which offers several weighting options: Huber, and bi-square among them.

Huber weights are appropriate when we don't have many extreme cases, and bisquare weights are best for those extreme cases. In either case, the algorithm operates in the same fashion, by using iteratively reweighted least squares (IRLS), which is described at the end of this recipe.

Getting ready

No special package is needed for this recipe.

...
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