Package: TrendTM 2.0.19
TrendTM: Trend of High-Dimensional Time Series Matrix Estimation
Matrix factorization for multivariate time series with both low rank and temporal structures. The procedure is the one proposed by Alquier, P. and Marie, N. Matrix factorization for multivariate time series analysis. Electronic journal of statistics, 13(2), 4346-4366 (2019).
Authors:
TrendTM_2.0.19.tar.gz
TrendTM_2.0.19.zip(r-4.5)TrendTM_2.0.19.zip(r-4.4)TrendTM_2.0.19.zip(r-4.3)
TrendTM_2.0.19.tgz(r-4.4-any)TrendTM_2.0.19.tgz(r-4.3-any)
TrendTM_2.0.19.tar.gz(r-4.5-noble)TrendTM_2.0.19.tar.gz(r-4.4-noble)
TrendTM_2.0.19.tgz(r-4.4-emscripten)TrendTM_2.0.19.tgz(r-4.3-emscripten)
TrendTM.pdf |TrendTM.html✨
TrendTM/json (API)
| # Install 'TrendTM' in R: |
| install.packages('TrendTM', repos = c('https://emilielebarbier74.r-universe.dev', 'https://cloud.r-project.org')) |
- Data_Series - Example of data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:853b0b43ef. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-win | OK | Nov 20 2024 |
| R-4.5-linux | OK | Nov 20 2024 |
| R-4.4-win | OK | Nov 20 2024 |
| R-4.4-mac | OK | Nov 20 2024 |
| R-4.3-win | OK | Nov 20 2024 |
| R-4.3-mac | OK | Nov 20 2024 |
Dependencies:ashbitopscapushecliclustercolorspacedeSolvefansifarverfdafdsFNNggplot2gluegtablehdrcdeisobandkernlabKernSmoothkslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmgcvmulticoolmunsellmvtnormnlmepcaPPpillarpkgconfigpracmaR6rainbowRColorBrewerRcppRCurlrlangscalessoftImputetibbleutf8vctrsviridisLitewithr
