Display the selection objective and fit measures associated with the estimation and model selection procedures.
This view is only available for equations estimated with elastic net, ridge regression, Lasso, and variable selection using Lasso.
Displays a table showing the model selection objective, number of non-zero coefficients, and the fit statistics (sum-of-squared residuals, mean-square error, R-squared, and adjusted R-squared) associated with the estimated model.
The row displaying the model selected optimal lambda will be highlighted.
Syntax
eq_name.modseltable(options)
Options
Examples
Consider the estimated elastic net equation
equation my_eq.enet(xtrans=none, lambdaratio=.0001, cvseed=513255899) lpsa c lcavol_s lweight_s age_s lbph_s svi_s lcp_s gleason_s pgg45_s
Then the command
my_eq.modseltable
displays the table showing the model selection objective and various fit statistics associated with each lambda in the path.
Cross-references
For further discussion, see
“Elastic Net and Lasso”.
The data underlying this table are available via the data member @modselresults.