Contents
Which is better for GLm 3 or 2 splines?
Yep, the 3 spline model has a much lower AIC despite using more model D.F., so is better. A nice feature of this cubic spline trick is that you can use it anywhere that takes a model matrix as input. So it will work with and any Bayesian GLM method you care to use.
Can a non linear spline be used in a GAM model?
But the splines trick is still handy. For instance, you can quickly modify an existing linear model to have a non-linear spline. Or use it in a Bayesian linear model that doesn’t have a GAM equivalent ( you can also spit out model matrices from mgcv and use them in Bayesian models if you want other types of splines).
How are B-splines used in linear modeling?
So fitting a b-spline means actually fitting a more complicated model. For this reason and the fact that b-splines can be poory behaved in the tails (Harrell, p. 24), most statisticians recommend working with natural splines. To wrap up, let’s go over some guidelines for using natural splines with real data.
Which is the most non linear line in GLM?
The blue line looks closest to the ‘true’ mean function (grey line). The purple and blue lines are our spline fits with 2 and 3 knots respectively. Both clearly capture the non-linearity. The grey line is the ‘true’ mean structure we created above. So our splines just peaks a bit too hard, but does get the shape right.
When to use a smoothing spline in R?
In order to fit more general sorts of GAMs, using smoothing splines or other components that cannot be expressed in terms of basis functions and then fit using least squares regression, we will need to use the gam library in R. The s () function, which is part of the gam library, is used to indicate that we would like to use a smoothing spline.
Where can I find splines and GAMS in R?
This lab on Splines and GAMs in R comes from p. 293-297 of “Introduction to Statistical Learning with Applications in R” by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani. It was re-implemented in Fall 2016 in tidyverse format by Amelia McNamara and R. Jordan Crouser at Smith College.