Hello all, I have columns of data that represent independent variables a,b,c and two dependent variables x,y in a non linear system. I want to be able to predict x and y given a,b,c. Matlab has a newrb function that does this well. I have not been able to find how to do it in Julia. I have looke…

[image] thomasjones: now say I have x,y,z data to predict a dependent variable w. how is that set up? how do I pass the values to the function? You just need an array of tuples, via xyz = tuple.(x,y,z), e.g. julia> x, y, z = rand(1000), rand(1000), rand(1000); julia> w = @. cos(x^2 - y * si…

[image] thomasjones: I have looked at Surrogates and basis function expansions and I can’t see how to set it up What have you tried, and what was the problem? Try to put together a minimal runnable example to illustrate what you are trying to do.

Thanks for the reply. I keep thinking it should be simple.One independent one dependent. I have data x vs y and I want to input x and get y. This works fine using Surrogates x=[0.0035, 0.0045, 0.0175, 0.0585, 0.068, 0.0935, 0.165, 0.2125, 0.241, 0.3615, 0.474, 0.4985, 0.5815, 0.646, 0.654, 0.723,…

This isn’t very clear in the Surrogates.jl documentation; if someone wants to make a PR to make the supported datastructures explicit that would be good.

Radial Basis interpolation multivariable

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stevengj June 3, 2022, 2:53pm 2

What have you tried, and what was the problem? Try to put together a minimal runnable example to illustrate what you are trying to do.

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Radial Basis interpolation multivariable

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