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Document Type

Campus-Only Access for Five (5) Years

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Mathematics

Year Degree Awarded

2015

Month Degree Awarded

September

First Advisor

Anna Liu

Subject Categories

Applied Statistics | Multivariate Analysis | Statistical Methodology | Statistical Models

Abstract

Single index varying coefficient model is a very attractive statistical model due to its ability to reduce dimensions and easy-of-interpretation. There are many theoretical studies and practical applications with it, but typically without features of variable selection, and no public software is available for solving it. Here we propose a new algorithm to fit the single index varying coefficient model, and to carry variable selection in the index part with LASSO. The core idea is a two-step scheme which alternates between estimating coefficient functions and selecting-and-estimating the single index. Both in simulation and in application to a Geoscience dataset, we showed that it works very well. We also presented our R package "sivcm" with the algorithm implemented and with ideas that can be extended beyond.

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