Detection of multiple undocumented change-points using adaptive Lasso

DOI10.1080/02664763.2013.862220zbMath1352.86020OpenAlexW2023482227MaRDI QIDQ3179235

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Publication date: 21 December 2016

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2013.862220

zbMATH Keywords

adaptive Lassomodel selection criterionmultiple undocumented change-pointsmultivariate \(t\) simultaneous confidence intervalssuccessive GLRT

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Geostatistics (86A32)

Related Items (3)

On optimal segmentation and parameter tuning for multiple change-point detection and inference ⋮ A comparison of single and multiple changepoint techniques for time series data ⋮ Semi-parametric segmentation of multiple series using a DP-Lasso strategy

Cites Work

• The Adaptive Lasso and Its Oracle Properties
• Degrees of freedom in lasso problems
• Sparse kernel learning with LASSO and Bayesian inference algorithm
• Least angle regression. (With discussion)
• Detection of multiple change-points in multivariate time series
• Detection and Correction of Artificial Shifts in Climate Series
• Spatial smoothing and hot spot detection for CGH data using the fused lasso
• The likelihood ratio test for a change-point in simple linear regression
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• A Cluster Analysis Method for Grouping Means in the Analysis of Variance
• New Weighted Portmanteau Statistics for Time Series Goodness of Fit Testing
• Multiple Change-Point Estimation With a Total Variation Penalty
• Mean shift testing in correlated data

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