ONE WAY FANOVA USING PENALIZED SPLINES

Other Titles
Abstract
There are several methods available for smoothing scatter-plots. One interesting method involves using mixed model techniques that can be shown to be equivalent to the penalized splines method. In order to analyze certain functional data sets, we propose an extension of this mixed model approach that involves the smoothing of several scatter-plots simultaneously. More precisely, we show how one can estimate the mean profiles of functional data that have one grouping factor by fitting a single mixed model. The underlying mixed model will then be used to set up a hypotheses testing scheme for doing one way functional analysis of variance, FANOVA. In doing so, we will establish an interesting connection between the one way FANOVA problem and the problem of testing whether variance components from certain mixed models are zero. Finally we will propose a method for doing multiple comparisons in the functional setting, again using the underlying mixed model from the fitting criteria. The proposed methods are then demonstrated through an analysis of a typical functional data set.
Journal / Series
Volume & Issue
Description
Sponsorship
Date Issued
2007-06-12T20:03:11Z
Publisher
Keywords
FANOVA; penalized splines; functional data; REML; scatter-plot smoothing; mixed model
Location
Effective Date
Expiration Date
Sector
Employer
Union
Union Local
NAICS
Number of Workers
Committee Chair
Committee Co-Chair
Committee Member
Degree Discipline
Degree Name
Degree Level
Related Version
Related DOI
Related To
Related Part
Based on Related Item
Has Other Format(s)
Part of Related Item
Related To
Related Publication(s)
Link(s) to Related Publication(s)
References
Link(s) to Reference(s)
Previously Published As
Government Document
ISBN
ISMN
ISSN
Other Identifiers
Rights
Rights URI
Types
dissertation or thesis
Accessibility Feature
Accessibility Hazard
Accessibility Summary
Link(s) to Catalog Record