Nonparametric multiple change point estimation in highly dependent time series

DOI10.1016/j.tcs.2015.10.041zbMath1343.62063OpenAlexW2176516221MaRDI QIDQ5964070

Daniil Ryabko, Azadeh Khaleghi

Publication date: 26 February 2016

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2015.10.041

zbMATH Keywords

consistencyunsupervised learningchange point analysisstationary ergodic time series

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Discrimination between B-processes is impossible
• The change-point problem for dependent observations
• Testing composite hypotheses about discrete ergodic processes
• Applications of Universal Source Coding to Statistical Analysis of Time Series
• Nonparametric Change-Point Estimation for Data from an Ergodic Sequence
• Nonparametric Statistical Inference for Ergodic Processes
• Information Theory and Statistics: A Tutorial
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