Memoize won't help for this as for any given set of data, the function will never be called twice with the same set of values. (Apart from the trivial case where the function is called with a single value. And in that case, the single value is return as a special case to end the recursion.)
For large datasets, Memoize would actually slow this function down by building a cache of values that would only ever be hit by chance. That chance, is if there exists two (or more) identical values in dataset.
Given the parameters are lists of floating point values with a continuous domain, "identical values" is an ethereal thing.
Also, the cache-key will be a function of both the number of values in the list, and their ordering. The size of the cache can quickly grow very large without ever providing payback.
Examine what is said, not who speaks.
"Efficiency is intelligent laziness." -David Dunham
"Think for yourself!" - Abigail
"Memory, processor, disk in that order on the hardware side. Algorithm, algorithm, algorithm on the code side." - tachyon
