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Coordinate optimization for generalized fused Lasso

Author

Listed:
  • M. Ohishi
  • K. Fukui
  • K. Okamura
  • Y. Itoh
  • H. Yanagihara

Abstract

Fused Lasso is one of extensions of Lasso to shrink differences of parameters. We focus on a general form of it called generalized fused Lasso (GFL). The optimization problem for GFL can be came down to that for generalized Lasso and can be solved via a path algorithm for generalized Lasso. Moreover, the path algorithm is implemented via the genlasso package in R. However, the genlasso package has some computational problems. Then, we apply a coordinate descent algorithm (CDA) to solve the optimization problem for GFL. We give update equations of the CDA in closed forms, without considering the Karush-Kuhn-Tucker conditions. Furthermore, we show an application of the CDA to a real data analysis.

Suggested Citation

  • M. Ohishi & K. Fukui & K. Okamura & Y. Itoh & H. Yanagihara, 2021. "Coordinate optimization for generalized fused Lasso," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(24), pages 5955-5973, November.
  • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:24:p:5955-5973
    DOI: 10.1080/03610926.2021.1931888
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