Date of Award

2010-01-01

Degree Name

Master of Science

Department

Mathematical Sciences

Advisor(s)

Ori Rosen

Abstract

Datasets often exhibit heavy tailed behavior and standard analyses are often heavily influenced by outliers. We propose a nonparametric regression model whose error term distribution is a mixture of a normal and a Student t distribution. This results in a model that is more resistant to outliers compared to a model with a normal error term.

Language

en

Provenance

Received from ProQuest

File Size

66 pages

File Format

application/pdf

Rights Holder

Courtney Marie Barnes

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