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 = c('https://cran.r-universe.dev', '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 5 months agofrom:0f36cc5522. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-linux | OK | Oct 30 2024 |
Exports:plotBetaplotModelSizeplotPIPsummaryBMAtopModelstracePlotULLGM_BMA
Dependencies:clicolorspacecrayonevaluatefansifarverggplot2gluegtablehighrhmsisobandknitrlabelinglatticelifecyclemagrittrMASSMatrixmgcvmnormtmunsellnlmepillarpkgconfigplyrprettyunitsprogressR6RColorBrewerRcppreshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithrxfunyaml