Book Image

R Statistics Cookbook

By : Francisco Juretig
2 (2)
Book Image

R Statistics Cookbook

2 (2)
By: Francisco Juretig

Overview of this book

R is a popular programming language for developing statistical software. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical procedures across your organization with the help of cutting-edge statistical tools. You'll start by implementing data modeling, data analysis, and machine learning to solve real-world problems. You'll then understand how to work with nonparametric methods, mixed effects models, and hidden Markov models. This book contains recipes that will guide you in performing univariate and multivariate hypothesis tests, several regression techniques, and using robust techniques to minimize the impact of outliers in data.You'll also learn how to use the caret package for performing machine learning in R. Furthermore, this book will help you understand how to interpret charts and plots to get insights for better decision making. By the end of this book, you will be able to apply your skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are extensively used in the data science industry.
Table of Contents (12 chapters)

Seasonality and SARIMAX models

In general, we will work with either quarterly, monthly, or weekly data. This is particularly interesting, because data arising from the same quarter/month/week will exhibit seasonal patterns. For example, if we are working with monthly sales of toys, we will see that they are usually bought in December as gifts. In consequence, all the data points related to December will be correlated. Seasonality terms have associated P/Q terms, which are analogous to their nonseasonal p/q counterparts.

Getting ready

In order to run this recipe, you will need to install the forecast package via install.packages("forecast").

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