An Application of Simplicial Intercept Depth (SID) Method for Fitting Linear Models

Abstract

This paper presents an application based on the Simplicial Intercept Depth method introduced by Liu (2004). We use this method to get the best linear fit of the phenotypic data for spot blotch resistant reaction of two different barley groups. The Simplicial Intercept Depth method is generalized by Simplicial Depth, also proposed by Liu in 1990. It provides a robust way for data analysis when outliers appear. In this paper, we use the Bootstrapping method, which is introduced by Bradley Efron (1979), to resample from the original dataset to get a distribution of the estimates. We also compare the SID with least squares regression and the Theil-type estimate which introduced by Shen (2009). The result shows that the SID is a robust method for estimating the coefficients of the linear regression model.