The Wikipedia page on R2 says $R^2$ can take on a value greater than 1. I don't see how this is possible.
Values of $R^2$ outside the range 0 to 1 can occur where it is used to measure the agreement between observed and modeled values and where the "modeled" values are not obtained by linear regression and depending on which formulation of $R^2$ is used. If the first formula above is used, values can be less than zero. If the second expression is used, values can be greater than one.
That quote refers to the "second expression" but I don't see a second expression on the page.
Is there any scenario where $R^2$ can be greater than 1? I am thinking about this question for nonlinear regression, but would like to get a general answer.
[For someone looking at this page with the opposite question in mind: Yes; $R^2$ can be negative. This happens when you fit a model that fits the data worse than a horizontal line. This would usually be due to a mistake in selecting a model or constraints.]