Robust model selection with flexible trimming

The forward search provides data-driven flexible trimming of a CpCp statistic for the choice of regression models that reveals the effect of outliers on model selection. An informed robust model choice follows. Even in small samples, the statistic has a null distribution indistinguishable from an FF distribution. Limits on acceptable values of the CpCp statistic follow. Two examples of widely differing size are discussed. A powerful graphical tool is the generalized candlestick plot, which summarizes the information on all forward searches and on the choice of models. A comparison is made with the use of MM-estimation in robust model choice.