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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

Product type Paperback

Published in Mar 2019

Publisher Packt

ISBN-13 9781789802566

Length 448 pages

Edition 1st Edition

Languages

R

Tools

ggplot

Concepts

Statistics

Author (1):

Francisco Juretig

View More author details

Table of Contents (12) Chapters

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

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Using a model for prediction

Once we have trained a model and recovered the marginal posterior densities, we will probably want to use our model for predicting/scoring new samples. This is not as easy as in the classical approach, because our parameters are no longer fixed values, but distributions. This means that the predictions won't be point estimates/values, but a range of possible values, each one of them with an associated probability.

Getting ready

We will use STAN, which can be installed via install.packages("rstan").

How to do it...

We will use...

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Authors (1)

Juretig

Juretig

Francisco Juretig has worked for over a decade in a variety of industries such as retail, gambling and finance deploying data-science solutions. He has written several R packages, and is a frequent contributor to the open source community.

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