Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Bayesian Analysis with Python

You're reading from   Bayesian Analysis with Python A practical guide to probabilistic modeling

Arrow left icon
Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781805127161
Length 394 pages
Edition 3rd Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Osvaldo Martin Osvaldo Martin
Author Profile Icon Osvaldo Martin
Osvaldo Martin
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface
1. Chapter 1 Thinking Probabilistically FREE CHAPTER 2. Chapter 2 Programming Probabilistically 3. Chapter 3 Hierarchical Models 4. Chapter 4 Modeling with Lines 5. Chapter 5 Comparing Models 6. Chapter 6 Modeling with Bambi 7. Chapter 7 Mixture Models 8. Chapter 8 Gaussian Processes 9. Chapter 9 Bayesian Additive Regression Trees 10. Chapter 10 Inference Engines 11. Chapter 11 Where to Go Next 12. Bibliography
13. Other Books You May Enjoy
14. Index

6.4 Splines

A general way to write very flexible models is to apply functions Bm to Xm and then multiply them by coefficients βm:

μ = 𝛽0 + 𝛽1B1 (X1) + 𝛽2B2(X2 )+ ⋅⋅⋅+ 𝛽mBm (Xm )

We are free to pick Bm as we wish; for instance, we can pick polynomials. But we can also pick other functions. A popular choice is to use B-splines; we are not going to discuss their definition, but we can think of them as a way to create smooth curves in such a way that we get flexibility, as with polynomials, but less prone to overfitting. We achieve this by using piecewise polynomials, that is, polynomials that are restricted to affect only a portion of the data. Figure 6.6 shows three examples of piecewise polynomials of increasing degrees. The dotted vertical lines show the ”knots,” which are the points used to restrict the regions, the dashed gray line represents the function we want to approximate, and the black lines are the piecewise polynomials.

PIC

Figure 6.6: Piecewise polynomials of increasing degrees

Figure 6.7 shows...

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 $19.99/month. Cancel anytime
Banner background image