mgcv.control {mgcv}R Documentation

Setting mgcv defaults


This is an internal function of package mgcv which allows control of the numerical options for fitting a generalized ridge regression problem using routine mgcv.




conv.tol The convergence tolerance.
max.half successive step halvings are employed if the Newton method and then the steepest descent backup fail to improve the UBRE/GCV score. This is how many to use before giving up.
target.edf If this is non-null it indicates that cautious optimization should be used, which opts for the local minimum closest to the target model edf if there are multiple local minima in the GCV/UBRE score.
min.edf Lower bound on the model edf. Useful for avoiding numerical problems at high smoothing parameter values. Negative for none.


Simon N. Wood


Gu and Wahba (1991) Minimizing GCV/GML scores with multiple smoothing parameters via the Newton method. SIAM J. Sci. Statist. Comput. 12:383-398

Wood, S.N. (2000) Modelling and Smoothing Parameter Estimation with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428

See Also


[Package mgcv version 1.3-23 Index]