Semiparametric regression is an extension of regression that permits incorporation
of flexible functional relationships using basis functions, such as splines and
wavelets, and penalties and is now well-developed for cross-sectional, longitudinal
and spatial data.
Almost all semiparametric regression analyses process the data in
batch. That is, a data set is fed into a semiparametric regression procedure at
some point in time after its collection.
This project focuses on doing semiparametric
regression in real time, with data processed as it is collected and made immediately
available via modern telecommunications technologies. Regression summaries may be
thought of as dynamic web-pages or iDevice apps rather than static tables and figures
on a piece of paper.