I am new to the use of cubic splines for regression purposes and wanted to find out
1) What is a good source (besides ESL which I read but am still uncertain) to learn about splines for regression?
2) How would you calculate the basis of a given natural cubic spline solution on new data? Specifically if one were to do the following:
data(iris) colnames(iris) Sepal.Length.ns<-ns(iris$Sepal.Length,df=5) Sepal.Length.ns
How would you take the information in Sepal.Length.ns (knots, boundaries) and compute the values for a new observation? The reason is to code this process outside of R, once fit in R initially (i.e. to put a regression model using cubic splines into a production system).
For example I can do this in R, but want to understand the calculation:
#three new observations to predict newVector<-c(4.45,3.35,2.2) pred.new<-predict(Sepal.Length.ns,newVector)