multiple correlation modification

Question

From wikipedia:

https://en.wikipedia.org/wiki/Multiple_correlation

In statistics, the coefficient of multiple correlation is a measure of how well a given variable can be predicted using a linear function of a set of other variables.

Is there a modification (standard names and methodology, python software) of multiple correlation where linear function is replaced with conic function? I.e., a linear function allows negative coefficients and conic function does not.

One possibility I could think of is to use mathematical programming to resolve this......

This might get more attention on mathematics.stackexchange.com — shadowtalker, Sep 20 '16 at 22:25
If you want a non-negative measure of association why not the coefficient of determination ($R^2$)? — Glen_b, Oct 19 '16 at 22:07

score 0 · Answer 1 · answered Nov 23 '21 at 18:54

0

If I understand this right, you can estimate a multiple regression model with non-negativity restrictions on the coefficients (in R, this can be done with, for instance ,the CRAN package nnls), and then use the R-squared from that fit.

answered Nov 23 '21 at 18:54

kjetil b halvorsen

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multiple correlation modification

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