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Activity Number: 445
Type: Contributed
Date/Time: Tuesday, August 2, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Learning and Data Science
Abstract #320464
Title: Estimating Coefficients of Direction in Single Index Model for Large $P$ Small $N$ Problem
Author(s): Jin Xie* and Xiangrong Yin
Companies: University of Kentucky and University of Kentucky
Keywords: Single Index Model ; Large $p$ small $n$ ; dimension reduction

In this article, we propose a new and simple method for estimating coefficient of the direction in single index model in the large $p$ small $n$ settings. Our proposed method enables existing approaches for $n>p$ to be adapted to the $n< p$ problems. Hence, we could obtain an estimate even if $n< p$. In addition, the method can successfully select important predictors. We provide theoretical proof for our algorithm. Simulations and real data analysis demonstrate the advantages of our method.

Authors who are presenting talks have a * after their name.

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