Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Data Analysis with R, Second Edition - Second Edition

You're reading from  Data Analysis with R, Second Edition - Second Edition

Product type Book
Published in Mar 2018
Publisher Packt
ISBN-13 9781788393720
Pages 570 pages
Edition 2nd Edition
Languages
Toc

Table of Contents (24) Chapters close

Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
1. RefresheR 2. The Shape of Data 3. Describing Relationships 4. Probability 5. Using Data To Reason About The World 6. Testing Hypotheses 7. Bayesian Methods 8. The Bootstrap 9. Predicting Continuous Variables 10. Predicting Categorical Variables 11. Predicting Changes with Time 12. Sources of Data 13. Dealing with Missing Data 14. Dealing with Messy Data 15. Dealing with Large Data 16. Working with Popular R Packages 17. Reproducibility and Best Practices 1. Other Books You May Enjoy Index

Interventions for improvement


Now, I know that so far in this book, we've approached automatic model selection techniques with a fair bit of healthy skepticism. In light of that, you might ask why I would spend time extolling the virtues of ets here all of a sudden.

While it's true that there's danger in automatic model selection – and we'll see an example of that later in this section – I'm more open to automated techniques for forecasting than for other domains. This is for two main reasons.

For one, in many of the sectors that employ forecasting, there is often a need to forecast estimations for a ton of different series, often, and at a high frequency basis. Think of an airline that has to set prices for flight tickets for hundreds of flights and update those prices on a daily (or even hourly) basis, based on projected consumer demand. Because of the intractability of hand-tuning models for each and every one of these series, many current approaches use in-house hard-coded algorithms for...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €14.99/month. Cancel anytime