Package: varband 0.9.0
varband: Variable Banding of Large Precision Matrices
Implementation of the variable banding procedure for modeling local dependence and estimating precision matrices that is introduced in Yu & Bien (2016) and is available at <https://arxiv.org/abs/1604.07451>.
Authors:
varband_0.9.0.tar.gz
varband_0.9.0.zip(r-4.7-x86_64)varband_0.9.0.zip(r-4.7-arm64)varband_0.9.0.zip(r-4.6-x86_64)varband_0.9.0.zip(r-4.6-arm64)varband_0.9.0.zip(r-4.5-x86_64)
varband_0.9.0.tgz(r-4.6-x86_64)varband_0.9.0.tgz(r-4.6-arm64)varband_0.9.0.tgz(r-4.5-x86_64)varband_0.9.0.tgz(r-4.5-arm64)
varband_0.9.0.tar.gz(r-4.7-arm64)varband_0.9.0.tar.gz(r-4.7-x86_64)varband_0.9.0.tar.gz(r-4.6-arm64)varband_0.9.0.tar.gz(r-4.6-x86_64)
varband_0.9.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
varband/json (API)
| # Install 'varband' in R: |
| install.packages('varband', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/hugogogo/varband/issues
archivedpackagesr-universeopenblascpp
Last updated from:81214ac2a8 (on package/varband). Checks:13 NOTE, 2 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | NOTE | 91 | ||
| linux-devel-x86_64 | NOTE | 131 | ||
| source / vignettes | OK | 194 | ||
| linux-release-arm64 | NOTE | 93 | ||
| linux-release-x86_64 | NOTE | 117 | ||
| macos-release-arm64 | NOTE | 81 | ||
| macos-release-x86_64 | NOTE | 203 | ||
| macos-oldrel-arm64 | NOTE | 112 | ||
| macos-oldrel-x86_64 | NOTE | 298 | ||
| windows-devel-arm64 | NOTE | 195 | ||
| windows-devel-x86_64 | NOTE | 147 | ||
| windows-release-arm64 | NOTE | 230 | ||
| windows-release-x86_64 | NOTE | 107 | ||
| windows-oldrel-x86_64 | NOTE | 106 | ||
| wasm-release | OK | 91 |
Exports:ar_genblock_diag_genmatimagesample_genvarbandvarband_cvvarband_genvarband_path
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generate an autoregressive model. | ar_gen |
| Generate a model with block-diagonal structure | block_diag_gen |
| Plot the sparsity pattern of a square matrix | matimage |
| Generate random samples. | sample_gen |
| Compute the varband estimate for a fixed tuning parameter value with different penalty options. | varband |
| Perform nfolds-cross validation | varband_cv |
| Generate a model with variable bandwidth. | varband_gen |
| Solve main optimization problem along a path of lambda | varband_path |