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Thee matrix 'D' from the Wendland chapter is of shape '# x Q', where '#' is the number of points within suitable radius of the input value and 'Q' is, for our purposes, equal to 'm+1', where 'm' is the degree of the MLS approximator. We need to make sure that delta and 'm+1' always behave such that the term 'P^T DP' is always invertible.
We should also have a test case that guarantees we catch this mode of failure.
The text was updated successfully, but these errors were encountered:
What your change currently does is cause the function to return a string. This itself causes issues.
According to Wendland, we can guarantee the invertibility of the term 'P^T DP' by making sure there are sufficiently many data points represented in D as rows. Happy to meet and talk about this if need be.
Thee matrix 'D' from the Wendland chapter is of shape '# x Q', where '#' is the number of points within suitable radius of the input value and 'Q' is, for our purposes, equal to 'm+1', where 'm' is the degree of the MLS approximator. We need to make sure that delta and 'm+1' always behave such that the term 'P^T DP' is always invertible.
We should also have a test case that guarantees we catch this mode of failure.
The text was updated successfully, but these errors were encountered: