Optimal change point detection and localization in sparse dynamic networks

DOI10.1214/20-aos1953zbMath1465.62154arXiv1809.09602OpenAlexW3127221797MaRDI QIDQ97726

Alessandro Rinaldo, Daren Wang, Yi Yu, Yi Yu, Daren Wang, Alessandro Rinaldo

Publication date: 1 February 2021

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1809.09602

zbMATH Keywords

stochastic block modelminimax optimalitychange point detectionlow-rank networks

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Minimax procedures in statistical decision theory (62C20) Economic time series analysis (91B84) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (12)

Discussion of `Detecting possibly frequent change-points: wild binary segmentation 2 and steepest-drop model selection' ⋮ Exact tests for offline changepoint detection in multichannel binary and count data with application to networks ⋮ Optimal multiple change-point detection for high-dimensional data ⋮ On change-point estimation under Sobolev sparsity ⋮ Univariate mean change point detection: penalization, CUSUM and optimality ⋮ Covariate-assisted matrix completion with multiple structural breaks ⋮ Time‐varying β‐model for dynamic directed networks ⋮ Unnamed Item ⋮ Localising change points in piecewise polynomials of general degrees ⋮ changepoints ⋮ Minimax rates in sparse, high-dimensional change point detection ⋮ Community detection on mixture multilayer networks via regularized tensor decomposition

Uses Software

• wbs

Cites Work

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