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LatentBMA
View on CRAN: Click
here
Download and install LatentBMA package within the R console
Install from CRAN:
install.packages("LatentBMA")
Install from Github:
library("remotes")
install_github("cran/LatentBMA")
Install by package version:
library("remotes")
install_version("LatentBMA", "0.1.1")
Attach the package and use:
library("LatentBMA")
Maintained by
Gregor Zens
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.LatentBMA . LatentBMA citation info . LatentBMA results . LatentBMA.pdf . Bayesian Model Averaging with 'LatentBMA' . LatentBMA_0.1.1.tar.gz . LatentBMA_0.1.1.zip . LatentBMA_0.1.1.zip . LatentBMA_0.1.1.zip . LatentBMA_0.1.1.tgz . LatentBMA_0.1.1.tgz . LatentBMA_0.1.1.tgz . LatentBMA_0.1.1.tgz . LatentBMA_0.1.1.tgz . LatentBMA_0.1.1.tgz . LatentBMA archive . https://CRAN.R-project.org/package=LatentBMA .
First Published: 2024-06-27
Latest Update: 2024-06-27
Description:
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.
How to cite:
Gregor Zens (2024). LatentBMA: Bayesian Model Averaging for Univariate Link Latent Gaussian Models. R package version 0.1.1, https://cran.r-project.org/web/packages/LatentBMA. Accessed 21 Feb. 2025.
Previous versions and publish date:
0.1.0 (2024-06-27 16:40)
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