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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

Computing ordinary least squares estimates

Ordinary least squares estimates are derived from minimizing the sum of the squared residuals. It can be proven that this minimisation leads to . It should be noted that we need to compute an inverse, and that can only be done if the determinant is different from zero. The determinant will be zero if there is a linear dependency between the variables.

It can also be proven that the beta coefficients are distributed according to a Gaussian distribution with variances equal to the diagonal elements of where is the estimated residual standard error.

How to do it...

In this exercise, we will simulate some data, and compute the estimates using both the lm function and doing the...

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