Currently the "Estimation Error" output is the second derivative of the optimization.
While this accurately characterizes the model optimization scheme, this is fairly useless to the user who is more likely
concerned with filtering out bad fitting models (not stably fitting models).
Thus I propose we make an option to add a column with the R^2 of the model.
Maybe this should be adjusted for the changing fitness mean?
Maybe some other metric that scales for high fit lineages getting a big R^2 despite large deviance?
Currently the "Estimation Error" output is the second derivative of the optimization.
While this accurately characterizes the model optimization scheme, this is fairly useless to the user who is more likely
concerned with filtering out bad fitting models (not stably fitting models).
Thus I propose we make an option to add a column with the R^2 of the model.
Maybe this should be adjusted for the changing fitness mean?
Maybe some other metric that scales for high fit lineages getting a big R^2 despite large deviance?