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Greetings, A couple general questions regarding the use of splines to interpolate depth profile data. Here is an example of a set of depths, with associated attributes for a given soil profile, along with a function for calculating midpoints from a set of soil horizon boundaries: #calculate midpoints: mid <- function(x) { for( i in 1:length(x)) { if( i > 1) { a[i] = (x[i] -

I think I have a spline problem, and I would like to implement the solution in S. There are a lot of spline algorithms and I am looking for some direction on what is most appropriate. I need a spline that can be made to extrapolate certain data points as described below. Of course it needs to happen algorithmically as I have lots of this data. Can a Bezier be fit to data? Consider a material

There is a very useful and apparently fundamental feature of R (or of the package pls) which I don't understand. For datasets with many independent (X) variables such as chemometric datasets there is a convenient formula and dataframe construction that allows one to access the entire X matrix with a single term. Consider the gasoline dataset available in the pls package. For the model