Menu Content/Inhalt
Seminars Print
previous year previous month next month next year
See by year See by month See by week See Today Search Jump to month
Aurore Delaigle, Melbourne Print
Friday, 01 April 2011, 15:15 - 16:15

Prediction in measurement error models

Aurore Delaigle, Melbourne University

Abstract: Predicting Y from a future X based on data (X_i,Y_i) is a fundamental inference problem. When X is observed accurately, the problem is that of standard regression estimation of E(Y|X). When the data X_i and future X are measured with error, prediction is sometimes less standard. With W denoting the future X measurement, prediction of Y requires estimation of E(Y|W). This is complicated when measurements are made under different conditions, so that errors in X_i and X are not identically distributed. We study this problem nonparametrically showing that convergence rates of estimators of E(Y|W) can vary from root-n to much slower nonparametric rates. We develop highly-adaptive, data-driven methods that perform well as illustrated by an interesting application in nutritional epidemiology.

Location: 2NO906, Plaine
Contact: This e-mail address is being protected from spam bots, you need JavaScript enabled to view it