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) <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:
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