School of Technology and Computer Science Seminars

Isotonic Regression

by Mr. Tapan Shah (School of Technology and Computer Science, TIFR)

Friday, September 27, 2013 from to (Asia/Kolkata)
at Colaba Campus ( D-405 (D-Block Seminar Room) )
Description
In statistical analysis,  regression is a widely used tool to get a functional relationship between observations of a response variable Y and covariate X. The goal is to estimate the regression function $$ m(X)=E[Y|X] $$. The estimation of m(·) is done by least-squares, where m(·) is an arbitrary function. In isotonic regression we restrict the function m(·) to be monotone. In this talk, we will look at a  geometrical method to find m(·)  and prove its optimality. This method leads to fast algorithm called Pooled Adjacent Value Algorithm (PAVA) which is widely used in statistical packages.