This book was written under the assumption that its readers have the following knowledge and skills:

• Basic knowledge of statistics or econometrics, which includes topics such as regression modeling, hypothesis testing, normal distribution, and so on
• Experience with R, or another programming language

You will need to have R installed (https://cran.r-project.org/) and it is recommended to install the RStudio IDE (https://www.rstudio.com/products/rstudio/).

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packt.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR/7-Zip for Windows
• Zipeg/iZip/UnRarX for Mac
• 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Hands-On-Time-Series-Analysis-with-R. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://www.packtpub.com/sites/default/files/downloads/9781788629157_ColorImages.pdf.

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "We will use the Sys.Date and Sys.time functions to pull date and time objects respectively."

A block of code is set as follows:

library(TSstudio)

data(USgas)

The output of the R code is prefixed by the ## sign:

ts_info(USgas)
##  The USgas series is a ts object with 1 variable and 227 observations
##  Frequency: 12 
##  Start time: 2000 1 
##  End time: 2018 11

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Select System info from the Administration panel."