Publication details

Shape analysis in the light of simplicial depth estimators

Investor logo

KATINA Stanislav

Year of publication 2010
Type Article in Proceedings
Conference Systems Biology & Statistical Bioinformatics
MU Faculty or unit

Faculty of Science

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.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.

More info