rstanbdp: Bayesian Deming Regression for Method Comparison (original) (raw)
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 |
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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 |
License: | GPL (≥ 3) |
NeedsCompilation: | yes |
SystemRequirements: | GNU make |
Materials: | README NEWS |
CRAN checks: | rstanbdp results |
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