Efficient Implementations of the Generalized Lasso Dual Path Algorithm.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS(2016)
摘要
We consider efficient implementations of the generalized lasso dual path algorithm given by Tibshirani and Taylor in 0022"> 2011. We first describe a generic approach that covers any penalty matrix D and any (full column rank) matrix X of predictor variables. We then describe fast implementations for the special cases of trend filtering problems, fused lasso problems, and sparse fused lasso problems, both with X = I and a general matrix X. These specialized implementations offer a considerable improvement over the generic implementation, both in terms of numerical stability and efficiency of the solution path computation. These algorithms are all available for use in the genlasso R package, which can be found in the CRAN repository.
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关键词
QR decomposition,Trend filtering,Laplacian linear systems,Fused lasso
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