Unbalanced ANOVA for Testing Shape Variability in Statistical Shape Analysis

Title & Authors
Unbalanced ANOVA for Testing Shape Variability in Statistical Shape Analysis
Kim, Jong-Geon; Choi, Yong-Seok; Lee, Nae-Young;

Abstract
Measures are very useful tools for comparing the shape variability in statistical shape analysis. For examples, the Procrustes statistic(PS) is isolated measure, and the mean Procrustes statistic(MPS) and the root mean square measure(RMS) are overall measures. But these measures are very subjective, complicated and moreover these measures are not statistical for comparing the shape variability. Therefore we need to study some tests. It is well known that the Hotelling's $\small{T^2}$ test is used for testing shape variability of two independent samples. And for testing shape variabilities of several independent samples, instead of the Hotelling's $\small{T^2}$ test, one way analysis of variance(ANOVA) can be applied. In fact, this one way ANOVA is based on the balanced samples of equal size which is called as BANOVA. However, If we have unbalanced samples with unequal size, we can not use BANOVA. Therefore we propose the unbalanced analysis of variance(UNBANOVA) for testing shape variabilities of several independent samples of unequal size.
Keywords
Hotelling's $\small{T^2}$ test;mean shape;shape variability;UNBANOVA;
Language
English
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