london dataset | Set DLNM parameters | Fit the model and posterior samples | Minimum mortality temperature | Predict exposure-lag-response effects | Plot
Package: bdlnm 0.1.1
Pau Satorra
bdlnm: Bayesian Distributed Lag Non-Linear Models (B-DLNM)
A Bayesian framework for estimating distributed lag linear and non-linear models. Model fitting is implemented using Integrated Nested Laplace Approximation (R package 'INLA'), together with prediction and visualization of exposure-lag-response associations. Additional functions allow estimation of optimal exposure values (e.g., minimum mortality temperature) and computation of attributable fractions and numbers. Models with 'crossbasis' or 'onebasis' terms are supported (R package 'dlnm').
Authors:
bdlnm_0.1.1.tar.gz
bdlnm_0.1.1.zip(r-4.7)bdlnm_0.1.1.zip(r-4.6)bdlnm_0.1.1.zip(r-4.5)
bdlnm_0.1.1.tgz(r-4.6-any)bdlnm_0.1.1.tgz(r-4.5-any)
bdlnm_0.1.1.tar.gz(r-4.7-any)bdlnm_0.1.1.tar.gz(r-4.6-any)
bdlnm_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bdlnm/json (API)
| # Install 'bdlnm' in R: |
| install.packages('bdlnm', repos = c('https://pasahe.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pasahe/bdlnm/issues
Pkgdown/docs site:https://pasahe.github.io
Datasets:
- london - London temperature and mortality data
Last updated from:536e1a9985. Checks:8 OK, 1 NOTE. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 322 | ||
| source / vignettes | OK | 183 | ||
| linux-release-x86_64 | OK | 317 | ||
| macos-release-arm64 | OK | 104 | ||
| macos-oldrel-arm64 | OK | 242 | ||
| windows-devel | NOTE | 78 | ||
| windows-release | OK | 102 | ||
| windows-oldrel | OK | 350 | ||
| wasm-release | OK | 138 |
Exports:attributablebcrosspredbdlnmcheck_inlaoptimal_exposure
Dependencies:bootclicrsdlnmlatticeMASSMatrixMatrixModelsmgcvnlmequantregSparseMsurvivaltsModel
