ProbBreed: Probability Theory for Selecting Candidates in Plant Breeding

Use probability theory under the Bayesian framework for calculating the risk of selecting candidates in a multi-environment context [Dias et al. (2022) <doi:10.1007/s00122-022-04041-y>]. Contained are functions used to fit a Bayesian multi-environment model (based on the available presets), extract posterior values and maximum posterior values, compute the variance components, check the model’s convergence, and calculate the probabilities. For both across and within-environments scopes, the package computes the probability of superior performance and the pairwise probability of superior performance. Furthermore, the probability of superior stability and the pairwise probability of superior stability across environments is estimated. A joint probability of superior performance and stability is also provided.

Depends: R (≥ 3.5.0)
Imports: ggplot2, rstan, rlang, lifecycle
Suggests: knitr, plotly, rmarkdown
Published: 2024-07-17
DOI: 10.32614/CRAN.package.ProbBreed
Author: Saulo Chaves ORCID iD [aut, cre], Kaio Dias ORCID iD [aut, cph], Matheus Krause ORCID iD [aut]
Maintainer: Saulo Chaves <saulo.chaves at>
License: AGPL (≥ 3)
NeedsCompilation: yes
Citation: ProbBreed citation info
Materials: README NEWS
CRAN checks: ProbBreed results


Reference manual: ProbBreed.pdf


Package source: ProbBreed_1.0.4.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): ProbBreed_1.0.4.0.tgz, r-oldrel (arm64): ProbBreed_1.0.4.0.tgz, r-release (x86_64): ProbBreed_1.0.4.0.tgz, r-oldrel (x86_64): ProbBreed_1.0.4.0.tgz
Old sources: ProbBreed archive


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