Package: LatentBMA 0.1.1

Gregor Zens
LatentBMA: Bayesian Model Averaging for Univariate Link Latent Gaussian Models
Bayesian model averaging (BMA) algorithms for univariate link latent Gaussian models (ULLGMs). For detailed information, refer to Steel M.F.J. & Zens G. (2024) "Model Uncertainty in Latent Gaussian Models with Univariate Link Function" <doi:10.48550/arXiv.2406.17318>. The package supports various g-priors and a beta-binomial prior on the model space. It also includes auxiliary functions for visualizing and tabulating BMA results. Currently, it offers an out-of-the-box solution for model averaging of Poisson log-normal (PLN) and binomial logistic-normal (BiL) models. The codebase is designed to be easily extendable to other likelihoods, priors, and link functions.
Authors:
LatentBMA_0.1.1.tar.gz
LatentBMA_0.1.1.tar.gz(r-4.5-noble)LatentBMA_0.1.1.tar.gz(r-4.4-noble)
LatentBMA_0.1.1.tgz(r-4.4-emscripten)LatentBMA_0.1.1.tgz(r-4.3-emscripten)
LatentBMA.pdf |LatentBMA.html✨
LatentBMA/json (API)
# Install 'LatentBMA' in R: |
install.packages('LatentBMA', repos = 'https://cloud.r-project.org') |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:0f36cc5522. Checks:3 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 29 2025 |
R-4.5-linux | OK | Mar 29 2025 |
R-4.4-linux | OK | Mar 29 2025 |
Exports:plotBetaplotModelSizeplotPIPsummaryBMAtopModelstracePlotULLGM_BMA
Dependencies:clicolorspacecrayonevaluatefansifarverggplot2gluegtablehighrhmsisobandknitrlabelinglatticelifecyclemagrittrMASSMatrixmgcvmnormtmunsellnlmepillarpkgconfigplyrprettyunitsprogressR6RColorBrewerRcppreshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithrxfunyaml
Citation
Steel MF, Zens G (2024). “Model Uncertainty in Latent Gaussian Models with Univariate Link Function.” arXiv Report. doi:10.48550/arXiv.2406.17318.
Corresponding BibTeX entry:
@Article{, title = {Model Uncertainty in Latent Gaussian Models with Univariate Link Function}, author = {Mark F.J. Steel and Gregor Zens}, year = {2024}, journal = {arXiv Report}, doi = {10.48550/arXiv.2406.17318}, }