Introduction | Data | Initialization | Estimation of $\pmb{\gamma^{\star}}$ | Variable selection | Illustration of the estimation of $\pmb{\beta^{\star}}$
Package: NBtsVarSel 1.0
NBtsVarSel: Variable Selection in a Specific Regression Time Series of Counts
Performs variable selection in sparse negative binomial GLARMA (Generalised Linear Autoregressive Moving Average) models. For further details we refer the reader to the paper Gomtsyan (2023), <arxiv:2307.00929>.
Authors:
NBtsVarSel_1.0.tar.gz
NBtsVarSel_1.0.zip(r-4.7-any)NBtsVarSel_1.0.zip(r-4.6-any)NBtsVarSel_1.0.zip(r-4.5-any)
NBtsVarSel_1.0.tgz(r-4.6-any)NBtsVarSel_1.0.tgz(r-4.5-any)
NBtsVarSel_1.0.tar.gz(r-4.7-any)NBtsVarSel_1.0.tar.gz(r-4.6-any)
NBtsVarSel_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
NBtsVarSel/json (API)
| # Install 'NBtsVarSel' in R: |
| install.packages('NBtsVarSel', repos = c('https://mgomtsyan.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- Y - Observation matrix Y
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:633b933f66. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 184 | ||
| source / vignettes | OK | 173 | ||
| linux-release | OK | 177 | ||
| macos-release | OK | 149 | ||
| macos-oldrel | OK | 113 | ||
| windows-devel | OK | 98 | ||
| windows-release | OK | 103 | ||
| windows-oldrel | OK | 96 | ||
| wasm-release | OK | 101 |
Exports:grad_hess_betagrad_hess_gammaNR_gammavariable_selection
Dependencies:bstclicodetoolscpp11doParallelfarverforeachgbmggplot2glmnetgluegtableisobanditeratorslabelinglatticelifecycleMASSMatrixmpathnumDerivpsclR6RColorBrewerRcppRcppEigenrlangrpartS7scalesshapesurvivalvctrsviridisLiteWeightSVMwithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Variable Selection in a Specific Regression Time Series of Counts | NBtsVarSel-package NBtsVarSel |
| Gradient and Hessian of the log-likelihood with respect to beta | grad_hess_beta |
| Gradient and Hessian of the log-likelihood with respect to gamma | grad_hess_gamma |
| Newton-Raphson method for estimation of gamma | NR_gamma |
| Variable selection | variable_selection |
| Observation matrix Y | Y |