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Comparison of several curves in the context of nonparametric regression

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Title: Comparison of several curves in the context of nonparametric regression
Author(s): Amarasinghe, Upali Ananda
Doctoral Committee Chair(s): Cox, Dennis D.
Department / Program: Statistics
Discipline: Statistics
Degree Granting Institution: University of Illinois at Urbana-Champaign
Degree: Ph.D.
Genre: Dissertation
Subject(s): Statistics
Abstract: Consider the model $y\sb{lj} = \mu\sb{l}(t\sb{j})$ + $\varepsilon\sb{lj}$, $l = 1,..,m$ and $j = 1,..,n,$ where $\varepsilon\sb{lj}$ are independent mean zero finite variance random variables. Under the above setting we test the hypotheses$H\sb0 : \mu\sb1 (t) {=..=}\ \mu\sb{m}(t)$ vs $H\sb{a} : \mu\sb{l}(t)$ are not all equal.Different procedures for testing the above hypotheses are studied. Test procedures are based on comparing estimates of the regression functions. Both smoothing spline and orthogonal series estimators are considered and the smoothing parameters are selected using Generalized Cross Validation criterion. Under some regularity conditions the asymptotic distributions of some of the test statistics are shown to be normal. Asymptotic power comparisons for the shift alternative are discussed. Comparison of regression curves in Bayesian nonparametric regression is also investigated.
Issue Date: 1991
Type: Text
Language: English
URI: http://hdl.handle.net/2142/21596
Rights Information: Copyright 1991 Amarasinghe, Upali Ananda
Date Available in IDEALS: 2011-05-07
Identifier in Online Catalog: AAI9210725
OCLC Identifier: (UMI)AAI9210725
 

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