Seminar: Yen-Chi Chen

June 26, 2017
Thursday, February 25, 2016 - 3:00pm
209 W. Eighteenth Ave. (EA), Room 170
Statistics Seminar Series

Title

Statistical Inference using Geometric Features

Speaker

Yen-Chi Chen, Carnegie Mellon University

Abstract

In many scientific studies, researchers are interested in geometric structure in the underlying density function. Common examples are local modes, ridges and level sets. In this talk, I will focus on two geometric structures: density ridges and modal regression. Density ridges are curve-like structures characterizing high density regions. I will first describe statistical models for ridges and then discuss their asymptotic theory and methods for constructing confidence sets. I will also show applications to astronomy.
 
Modal regression is an alternative way to study the conditional structure of the response variable given covariates. Instead of estimating the conditional expectation, modal regression focuses on conditional local modes. I will present several useful statistical properties for modal regression, including asymptotic theory, confidence sets, prediction sets and clustering.
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