Shape analysis in the light of simplicial depth estimators
| Authors | |
|---|---|
| Year of publication | 2010 |
| Type | Article in Proceedings |
| Conference | Systems Biology & Statistical Bioinformatics |
| MU Faculty or unit | |
| Citation | |
| Web | http://www1.maths.leeds.ac.uk/statistics/workshop/lasr2007/proceedings/ |
| Field | Applied statistics, operation research |
| Keywords | simplicial depth; shape analysis |
| Description | In this paper we present the maximum simplicial depth estimator and compare it to the ordinary least square estimator in examples from 2D shape analysis focusing on bivariate and multivariate allometrical problems from zoology. We compare two types of estimators derived under different subsets of parametric space on the basis of the linear regression model. In applications where outliers in the x- or y-axis direction occur in the data and residuals from ordinary least-square (OLS) linear regression model are not normally distributed, we recommend the use of the maximum simplicial depth estimators. |
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