Model Uncertainty in Poisson Log-Normal Regression Models | Estimating a Binomial Logistic-Normal Regression Model | Summarizing the Estimation Output | Further Customization
Package: LatentBMA 0.1.3
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_0.1.3.tar.gz
LatentBMA_0.1.3.tar.gz(r-4.7-any)LatentBMA_0.1.3.tar.gz(r-4.6-any)
LatentBMA_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
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 from:7ca43065c1. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 131 | ||
| source / vignettes | OK | 188 | ||
| linux-release-x86_64 | OK | 127 | ||
| wasm-release | OK | 114 |
Exports:plotBetaplotModelSizeplotPIPsummaryBMAtopModelstracePlotULLGM_BMA
Dependencies:clicpp11crayonevaluatefarverggplot2gluegtablehighrhmsisobandknitrlabelinglifecyclemagrittrmnormtpkgconfigplyrprettyunitsprogressR6RColorBrewerRcppreshape2rlangS7scalesstringistringrvctrsviridisLitewithrxfunyaml
