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/>.
Version: 0.0.3 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) Published: 2024-07-26 DOI: 10.32614/CRAN.package.rstanbdp Author: Giorgio Pioda [aut, cre] Maintainer: Giorgio Pioda <gfwp at ticino.com> License: GPL (≥ 3) NeedsCompilation: yes SystemRequirements: GNU make Materials: README NEWS CRAN checks: rstanbdp results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=rstanbdp to link to this page.
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