Cross Validated Asked on January 3, 2021

I’m not very familiar with the process for solving tensor product basis fittings. I’ve done some work with fitting an ispline basis with a non-negative-least-squares solver to fit a monotonic spline to noisy data where the underlying function is guaranteed to be monotonic.

Now I’m interested in taking a tensor product of this ispline basis with a bspline basis. But I’m not certain the best way to do this and still enforce the non-negative constraint. My one thought is to double each of the b-spline basis with its negative. I can take the tensor product of this with the ispline basis, then I should still be able to use a non-negative-least-squares solver. Is this a reasonable approach? Is there a better approach?

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