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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:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=rstanbdp
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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