tsBSS
Blind Source Separation and Supervised Dimension Reduction for Time Series
Different estimators are provided to solve the blind source separation problem for multivariate time series with stochastic volatility and supervised dimension reduction problem for multivariate time series. Different functions based on AMUSE and SOBI are also provided for estimating the dimension of the white noise subspace. The package is fully described in Nordhausen, Matilainen, Miettinen, Virta and Taskinen (2021) doi:10.18637/jss.v098.i15.
- Version1.0.0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- tsBSS citation info
- Last release07/10/2021
Documentation
Team
Markus Matilainen
Klaus Nordhausen
Show author detailsRolesAuthorJoni Virta
Show author detailsRolesAuthorJari Miettinen
Hannu Oja
Show author detailsRolesAuthorSara Taskinen
Christophe Croux
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 276 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 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 4,392 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 54 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.
Data provided by CRAN
Binaries
Dependencies
- Depends3 packages
- Imports5 packages
- Suggests4 packages
- Linking To2 packages
- Reverse Depends1 package
- Reverse Imports1 package