Mathematical Sciences: Complexity and Information Based Criteria for Model Selection

这项研究将处理用于模型选择的信息的属性。已经制定了新的信息标准，处理多个数据集和/或可能具有相同维度的模型的情况。这项研究将在这些标准的最新结果的基础上进行扩展，特别是将建立渐近性质。这项研究将涉及统计模型的选择。一般说来，该领域关注的是在一组候选模型中选择最适合数据集的模型。令人感兴趣的问题包括过拟合和回归变量的选择问题。

This research will deal with the properties of information as used in model selection. New information criteria have been developed which deal with situations of multiple data sets and/or with models which may have the same dimension. This research will expand on recent results for these criteria, and in particular will establish asymptotic properties. This research will deal with statistical model selection. The area, generally speaking, is concerned with the choice of the best model to fit a dat set among a set of candidate models. Issues of interest include problems of overfitting and the selection of variables in regression.