6.2.2.2.1.1.3. statsmodels.sandbox.datarich.factormodels.FactorModelUnivariate.fit_find_nfact

FactorModelUnivariate.fit_find_nfact(maxfact=None, skip_crossval=True, cv_iter=None)

estimate the model and selection criteria for up to maxfact factors

The selection criteria that are calculated are AIC, BIC, and R2_adj. and additionally cross-validation prediction error sum of squares if skip_crossval is false. Cross-validation is not used by default because it can be time consuming to calculate.

By default the cross-validation method is Leave-one-out on the full dataset. A different cross-validation sample can be specified as an argument to cv_iter.

Results are attached in results_find_nfact