decp
Complete Change Point Analysis
Provides a comprehensive approach for identifying and estimating change points in multivariate time series through various statistical methods. Implements the multiple change point detection methodology from Ryan & Killick (2023) doi:10.1080/00401706.2023.2183261 and a novel estimation methodology from Fotopoulos et al. (2023) doi:10.1007/s00362-023-01495-0 generalized to fit the detection methodologies. Performs both detection and estimation of change points, providing visualization and summary information of the estimation process for each detected change point.
- Version0.1.2
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release08/22/2024
Team
Vasileios Pavlopoulos
Hieu Pham
Show author detailsRolesAuthor, ContributorParas Bhatt
Show author detailsRolesAuthor, ContributorYi Tan
Show author detailsRolesAuthor, ContributorRavi Patnayakuni
Show author detailsRolesAuthor, Contributor
Insights
Last 30 days
This package has been downloaded 172 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,977 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 23, 2024 with 48 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports6 packages