Heather Battey

Large numbers of explanatory variables

The lasso and its variants are powerful methods for regression analysis
when there are a small number of study individuals and a large number of
potential explanatory variables. There results a single model, while
there may be several models equally compatible with the data. I will
outline a different approach whose aim is essentially a confidence set
of effective simple representations. A probabilistic assessment of the method will be given.

The talk is based on joint work with David R Cox