Fixed Point Clusters for Linear Regression: Computation and Comparison
- Cite this article as:
- Hennig, C. J. of Classification (2002) 19: 249. doi:10.1007/s00357-001-0045-7
In this paper an algorithm is developed, which aims to find all FPCs of a dataset corresponding to well separated linear regression subpopulations. Its ability to find such subpopulations under the occurence of outliers is compared to methods based on ML-estimation of mixture models by means of a simulation study. Furthermore, FPC analysis is applied to a real dataset.