Smoothing Spline ANOVA Models by Chong Gu, published by Springer
I am intrigued by this book. Splines were my favorite thing in graduate school. I have made a lot of ANOVA models. It is fun to see what I tried to do finally achieved.
Smoothing Splines ANOVA Models uses R as the programming language. Great to see in a book are in depth proofs and R code.
Chapter 3.3 shows how to draw Bayesian confidence intervals in R.
Chapter 3.10.1 discusses the difference between natural splines and B splines. That B splines have different boundary conditions.
There is code for doing cubic splines with a jump. Something that you run into with real data.
In Chapter 8.63 about hazard functions and the Weibull family has code for cubic spline Weibull regression with censored and truncated data.
I am enjoying reading this book. The code works and the examples are easy to understand.