A Minimal Book Example
1
Intro & Motivation
2
What is a linear Model?
2.1
General formulation
2.2
The least squares problem
3
Methods for solving linear models
3.1
Closed form solution
3.2
Iterative methods
3.3
Decomposition methods
4
How R solves linear models
4.1
R
4.2
What’s the goal?
4.2.1
Walking through the function calls
4.2.2
Cleanup work and defensive programming
4.2.3
Specifying the design matrix
4.2.4
Calculating the regression coefficients – lm.fit
4.3
C
4.4
Fortran
4.4.1
QR decomposition
4.5
The machine code
5
Appendix A1 – Linear Algebra Concepts
6
Apendix A2 – An Aside on Optimizers
7
Apendix A3 – Other decomposition techniques
8
Apendix A4 – rogramming tidbits
8.1
The Ellipsis
8.2
match.call()
Published with bookdown
How does R fit a linear model?
Chapter 3
Methods for solving linear models
3.1
Closed form solution
3.2
Iterative methods
3.3
Decomposition methods