Penalized likelihood approaches for high-dimensional model selection

Axel Benner
One important topic of current research on observational and especially prognostic factor studies is the development of methods that can be employed to analyse high-dimensional data, where the number of explanatory variables is much larger than the number of observations. This is mainly driven by the[for full text, please go to the a.m. URL]