nonstat
0.0.6Detecting Nonstationarity in Time Series
Overview
Provides a nonvisual procedure for screening time series for nonstationarity in the context of intensive longitudinal designs, such as ecological momentary assessments. The method combines two diagnostics: one for detecting trends (based on the split R-hat statistic from Bayesian convergence diagnostics) and one for detecting changes in variance (a novel extension inspired by Levene's test). This approach allows researchers to efficiently and reproducibly detect violations of the stationarity assumption, especially when visual inspection of many individual time series is impractical. The procedure is suitable for use in all areas of research where time series analysis is central. For a detailed description of the method and its validation through simulations and empirical application, see Zitzmann, S., Lindner, C., Lohmann, J. F., & Hecht, M. (2024) "A Novel Nonvisual Procedure for Screening for Nonstationarity in Time Series as Obtained from Intensive Longitudinal Designs" https://www.researchgate.net/publication/384354932_A_Novel_Nonvisual_Procedure_for_Screening_for_Nonstationarity_in_Time_Series_as_Obtained_from_Intensive_Longitudinal_Designs.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
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- Documented parameters
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- Return-value docs
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- References docs
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Code & Tests
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.0.6Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-04-01
- Total releases
- 1 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 3.8 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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