Graph-based change-point detection
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Publication:2338923
DOI10.1214/14-AOS1269zbMath1308.62090arXiv1209.1625MaRDI QIDQ2338923
Publication date: 27 March 2015
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1209.1625
tail probabilityhigh-dimensional datanonparametricschange-pointnetwork datagraph-based testsscan statisticcomplex datanon-Euclidean data
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Sequential change-point detection in high-dimensional Gaussian graphical models ⋮ Exact tests for offline changepoint detection in multichannel binary and count data with application to networks ⋮ Testing for dependence on tree structures ⋮ A refined Cramér-type moderate deviation for sums of local statistics ⋮ On change-point estimation under Sobolev sparsity ⋮ Compound Sequential Change-point Detection in Parallel Data Streams ⋮ ClaSP: parameter-free time series segmentation ⋮ Break point detection for functional covariance ⋮ A Normality Test for High-dimensional Data Based on the Nearest Neighbor Approach ⋮ Hypothesis testing for populations of networks ⋮ A generalized knockoff procedure for FDR control in structural change detection ⋮ Limiting distributions of graph-based test statistics on sparse and dense graphs ⋮ Latent Space Model for Higher-Order Networks and Generalized Tensor Decomposition ⋮ Confidence distributions for change-points and regime shifts ⋮ Change point detection for high dimensional data via kernel measure with application to human aging brain data ⋮ Asymptotic distribution-free change-point detection for multivariate and non-Euclidean data ⋮ CUSUM multi-chart for detecting unknown abrupt changes under finite measure space for network observation sequences ⋮ Fréchet change-point detection ⋮ A Kernel Multiple Change-point Algorithm via Model Selection ⋮ Unnamed Item ⋮ Nonparametric maximum likelihood approach to multiple change-point problems ⋮ Asymptotic distribution-free change-point detection based on interpoint distances for high-dimensional data ⋮ High dimensional change point inference: recent developments and extensions ⋮ Multiscale change-point segmentation: beyond step functions ⋮ Graph-based change-point detection ⋮ Functional convergence of sequential \(U\)-processes with size-dependent kernels
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