Coordinate optimization for generalized fused Lasso

M. Ohishi, K. Fukui, K. Okamura, Y. Itoh and H. Yanagihara

Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 24, 5955-5973

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.

Date: 2021
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DOI: 10.1080/03610926.2021.1931888

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