Hi,

I have questions about R2 used in pls (or multivariate analysis).

Is R2 same with the square of the PCC (Pearson Correlation Coefficient)?

I found the following description from wiki (Coefficient of determination)

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Similarly, in linear least squares regression with an estimated intercept
term, R2 equals the square of the Pearson correlation coefficient between
the observed and modeled (predicted) data values of the dependent variable.
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If so, Q2 (R2 of cross validation) should range between 0 and 1.
But it doesn't. I got negative values of Q2 when running my dataset.
Of course, from the definition of Q2, Q2 can be negative when my model is
not at all predictive.

My question is what the relationship between R2 and pcc^2 is.

Euna

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