Linear grouping using orthogonal regression

@article{Aelst2006LinearGU,
  title={Linear grouping using orthogonal regression},
  author={Stefan Van Aelst and Xiaogang Wang and Ruben H. Zamar and Rong Zhu},
  journal={Computational Statistics & Data Analysis},
  year={2006},
  volume={50},
  pages={1287-1312}
}
This paper proposes a new method, called linear grouping algorithm (LGA), to detect different linear structures in a data set. LGA is useful for investigating potential linear patterns in datasets, that is, subsets that follow different linear relationships. LGA combines ideas from principal components, clustering methods and resampling algorithms. It can detect several different linear relations at once. We also propose methods to determine the number of groups in the data and diagnostic tools… CONTINUE READING

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