TSMCP
1.1Fast Two Stage Multiple Change Point Detection
Overview
A novel and fast two stage method for simultaneous multiple change point detection and variable selection for piecewise stationary autoregressive (PSAR) processes and linear regression model. It also simultaneously performs variable selection for each autoregressive model and hence the order selection.
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
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 100%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.1Latest
- unarchivedReturned to CRAN2025-11-03
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- archivedRemoved from CRAN2022-05-23requires archived package 'plus'
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 1.02018-11-18
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-11-18
- Total releases
- 2 / 8 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.3.0
- Download size
- 8.0 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("TSMCP")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
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