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@lenthomas: "Yes, I think this is an excellent idea for a feature enhancement. One could imagine fitting all the models up to max_adjustments (so that the fitted values of one are used as the start values for the next, except for the new parameter), and then calculating c_hat1 using the most complex one, and then doing model selection. It'd be good if it stored the c_hat1 somewhere as well (perhaps an attribute) and adds that to the printed output from the print and summary methods."
The text was updated successfully, but these errors were encountered:
per #132
@lenthomas: "Yes, I think this is an excellent idea for a feature enhancement. One could imagine fitting all the models up to
max_adjustments
(so that the fitted values of one are used as the start values for the next, except for the new parameter), and then calculatingc_hat1
using the most complex one, and then doing model selection. It'd be good if it stored thec_hat1
somewhere as well (perhaps an attribute) and adds that to the printed output from the print and summary methods."The text was updated successfully, but these errors were encountered: