rstanbdp: Bayesian Deming Regression for Method Comparison

Regression methods to quantify the relation between two measurement methods are provided by this package. The focus is on a Bayesian Deming regressions family. With a Bayesian method the Deming regression can be run in a traditional fashion or can be run in a robust way just decreasing the degree of freedom d.f. of the sampling distribution. With d.f. = 1 an extremely robust Cauchy distribution can be sampled. Moreover, models for dealing with heteroscedastic data are also provided. For reference see G. Pioda (2024) <>.

Version: 0.0.2
Depends: R (≥ 3.5.0)
Imports: methods, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), rstantools (≥ 2.4.0), rrcov, mixtools, bayestestR, KernSmooth
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥, RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Published: 2024-02-23
Author: Giorgio Pioda ORCID iD [aut, cre]
Maintainer: Giorgio Pioda <gfwp at>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README NEWS
CRAN checks: rstanbdp results


Reference manual: rstanbdp.pdf


Package source: rstanbdp_0.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): rstanbdp_0.0.2.tgz, r-oldrel (arm64): rstanbdp_0.0.2.tgz, r-release (x86_64): rstanbdp_0.0.2.tgz


Please use the canonical form to link to this page.