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Group LASSO for Change-points in Functional Time Series
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作者 chang xiong chi Rong Mao ZHANG 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2023年第11期2075-2090,共16页
Multiple change-points estimation for functional time series is studied in this paper.The change-point problem is first transformed into a high-dimensional sparse estimation problem via basis functions.Group least abs... Multiple change-points estimation for functional time series is studied in this paper.The change-point problem is first transformed into a high-dimensional sparse estimation problem via basis functions.Group least absolute shrinkage and selection operator(LASSO)is then applied to estimate the number and the locations of possible change points.However,the group LASSO(GLASSO)always overestimate the true points.To circumvent this problem,a further Information Criterion(IC)is applied to eliminate the redundant estimated points.It is shown that the proposed two-step procedure estimates the number and the locations of the change-points consistently.Simulations and two temperature data examples are also provided to illustrate the finite sample performance of the proposed method. 展开更多
关键词 Basis function CHANGE-POINT functional time series information criterion group LASSO(GLASSO)
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