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It it possible to use an absolute errors approach to optimize a nonlinear modle in JMP?

I think the answer to this question is no, as according to my JMP 7 Statistics and Graphing guide (in reference to loss functions for nonlinear modeling):

"(The Loss Function) must have non-zero first and second-order derivatives."

The ABS() function, as it is linear, has a zero second derivative. So, it would seem that the algorithm that JMP uses does not work if you want to use an absolute errors approach. However, I wanted to check as absolute errors isn't all that rare to use, so is it possible that there is some way to work around this?



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