Change-point detection in multinomial data with a large number of categories
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Publication:1800792
DOI10.1214/17-AOS1610zbMath1408.62110OpenAlexW2788498295MaRDI QIDQ1800792
Guosheng Yin, Changliang Zou, Guang-Hui Wang
Publication date: 24 October 2018
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.aos/1534492827
asymptotic normalitymultiple change-point detectioncategorical datasparse contingency tablehigh-dimensional homogeneity test
Asymptotic properties of nonparametric inference (62G20) Hypothesis testing in multivariate analysis (62H15) Contingency tables (62H17)
Related Items (8)
Multiscale Quantile Segmentation ⋮ The CUSUM statistics of change-point models based on dependent sequences ⋮ On asymptotic approximation of ratio models for weakly dependent sequences ⋮ Data-driven selection of the number of change-points via error rate control ⋮ Change-point testing for parallel data sets with FDR control ⋮ Consistent selection of the number of change-points via sample-splitting ⋮ Sequential change-point detection in a multinomial logistic regression model ⋮ Outlier detection for multinomial data with a large number of categories
Uses Software
Cites Work
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