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impala: Bayesian Model Calibration

Package provides tools for modular Bayesian model calibration. these tools allow for posterior exploration with sampling methods including tempering and adaptive Markov Chain Monte Carlo (MCMC). Allows for pooled calibration or hierarchal calibration of parameters. For more information see Francom et al., 2025 <doi:10.1137/24M1644092>.

Version: 0.1.0
Imports: cli, methods, progress, einsum
Suggests: fdasrvf, BASS, BayesPPR, mvBayes, coda, bayesplot, gridExtra, hexbin, knitr, rmarkdown
Published: 2026-06-19
DOI: 10.32614/CRAN.package.impala
Author: J. Derek Tucker ORCID iD [aut, cre], Sandia National Laboratories [cph, fnd]
Maintainer: J. Derek Tucker <jdtuck at sandia.gov>
BugReports: https://github.com/sandialabs/rImpala/issues
License: MIT + file LICENSE
URL: https://github.com/sandialabs/rImpala
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: impala results

Documentation:

Reference manual: impala.html , impala.pdf
Vignettes: example (source, R code)

Downloads:

Package source: impala_0.1.0.tar.gz
Windows binaries: r-devel: impala_0.1.0.zip, r-release: impala_0.1.0.zip, r-oldrel: impala_0.1.0.zip
macOS binaries: r-release (arm64): impala_0.1.0.tgz, r-oldrel (arm64): impala_0.1.0.tgz, r-release (x86_64): impala_0.1.0.tgz, r-oldrel (x86_64): impala_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=impala to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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