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Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators

Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators

Axel Bücher
Holger Dette
Florian Heinrichs
ArXiv (abs)PDFHTML

Papers citing "Are deviations in a gradually varying mean relevant? A testing approach based on sup-norm estimators"

6 / 6 papers shown
Title
Detecting relevant deviations from the white noise assumption for non-stationary time series
Detecting relevant deviations from the white noise assumption for non-stationary time series
Patrick Bastian
59
0
0
11 Nov 2024
OML-AD: Online Machine Learning for Anomaly Detection in Time Series Data
OML-AD: Online Machine Learning for Anomaly Detection in Time Series Data
Sebastian Wette
Florian Heinrichs
AI4TS
74
1
0
15 Sep 2024
Gradual changes in functional time series
Gradual changes in functional time series
Patrick Bastian
Holger Dette
AI4TS
106
3
0
10 Jul 2024
Monitoring Machine Learning Models: Online Detection of Relevant Deviations
Monitoring Machine Learning Models: Online Detection of Relevant Deviations
Florian Heinrichs
54
3
0
26 Sep 2023
Predictive change point detection for heterogeneous data
Predictive change point detection for heterogeneous data
Anna-Christina Glock
F. Sobieczky
Johannes Furnkranz
Peter Filzmoser
M. Jech
61
1
0
11 May 2023
A distribution free test for changes in the trend function of locally stationary processes
A distribution free test for changes in the trend function of locally stationary processes
Holger Dette
Florian Heinrichs
32
6
0
22 May 2020