Imprecise Regression

Imprecise regression is a generalization of linear regression that gives us stronger tools for modeling uncertainty. In a typical linear regression setting, we consider the input data to be precise observations: single points. In imprecise regression, we generalize the notion of observations to intervals rather than points. This allows us to more accurately represent scenarios with measurement error or other sources of uncertainty that make our input data “fuzzy”. This tutorial is based on the imprecise regression work in Cattaneo and Wiencierz (2012) and will teach you the fundamentals of this technique.