Bayesian Deming Regression for Method Comparison R package rstanbdp version 0.0.3 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) <https://piodag.github.io/bd1/>. Software 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 (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0) Giorgio Pioda <gfwp@ticino.com> Comprehensive R Archive Network (CRAN) Giorgio Pioda [aut, cre] (ORCID: <https://orcid.org/0000-0002-8714-8678>) GPL (>= 3) 2024-07-26 application/tgz https://CRAN.R-project.org/package=rstanbdp doi:10.32614/CRAN.package.rstanbdp