Directed Regression

Stanford University, Stanford CA

Investigators

Abstract

The research objective of this project is to develop efficient regression algorithms for fitting models that are to be used to guide subsequent decisions. Linear regression algorithms will be designed for static models that support repeated decisions as well as for linear time series models that support dynamic decisions. Logistic regression algorithms will be designed to accommodate use of discrete choice data. The algorithms will take as input decision objectives in addition to data and a model specification. If successful, new algorithms resulting from this research project will enhance, relative to more standard regression algorithms, the quality of decisions made using regression models when selected features do not perfectly capture relationships present in systems that generate data.