Package: bayesammi
Type: Package
Title: Bayesian Estimation of the Additive Main Effects and
        Multiplicative Interaction Model
Version: 1.0.0
Date: 2026-11-04
Authors@R: c(
      person(c("Muhammad"), "Yaseen", email = "myaseen208@gmail.com", role = c("aut", "cre"),
             comment = c(ORCID = "0000-0002-5923-1714"))
    , person("Jose", "Crossa", email = "j.crossa@cgiar.org", role = c("aut", "ctb"))
    , person("Sergio", "Perez-Elizalde", email = "sergiop@colpos.mx", role = c("aut", "ctb"))
    , person("Diego", "Jarquin", email = "diego.jarquin@gmail.com", role = c("aut", "ctb"))
    , person(c("Jose", "Miguel"), "Cotes", email = "jmcotes@unal.edu.co", role = c("aut", "ctb"))
    , person("Kert", "Viele", email = "kert@berryconsultants.net", role = c("aut", "ctb"))
    , person("Genzhou", "Liu", role = c("aut", "ctb"))
    , person(c("Paul", "L."), "Cornelius", role = c("aut", "ctb"))
    , person(c("Julian", "Garcia"), "Abadillo Velasco", email = "garciaabadillo.j@ufl.edu", role = c("aut", "ctb"))
    )
Description: Bayesian estimation of the additive main effects and
    multiplicative interaction (AMMI) model of multi-environment trials by
    the Gibbs sampler of Crossa, Perez-Elizalde, Jarquin, Cotes, Viele, Liu
    and Cornelius (2011) <doi:10.2135/cropsci2010.06.0343>: posterior
    distributions of the overall mean, genotype and environment effects,
    singular values, genotype and environment scores (von Mises-Fisher
    conditionals on the constrained spheres) and error variance; several
    chains with burn-in and thinning; posterior summaries with highest
    posterior density intervals; the convergence diagnostics of
    Raftery-Lewis, Heidelberger-Welch and Gelman-Rubin; the AMMI biplot with
    highest posterior density regions for inference on genotypes and
    environments; least-squares AMMI; and a plain-language interpretation of
    every result, computed from its numbers. Beyond the article: unbalanced
    trials with missing plots and cells (data augmentation),
    environment-specific error variances, the Bayesian GGE (sites
    regression) model of Perez-Elizalde, Jarquin and Crossa (2012)
    <doi:10.1007/s13253-011-0063-9>, probabilities of superior performance
    and stability (Dias et al. 2022 <doi:10.1007/s00122-022-04041-y>),
    posterior ranks, Bayesian stability measures, predictions and the
    winner of every environment, model choice by DIC and WAIC with
    posterior predictive checks, draws for the 'posterior', 'bayesplot'
    and 'coda' packages, a compiled sampler, and a built-in 'shiny'
    application. Bayesian stability analysis: the Finlay-Wilkinson,
    Eberhart-Russell and Shukla models by Gibbs sampling, and the posterior
    distributions of classical stability indices (Wricke, Shukla, Lin-Binns,
    Annicchiarico, Eskridge's safety-first) and of AMMI-based indices (ASV,
    SIPC, EV, Za, WAAS, WAASY). Every result prints the references of its
    method.
License: GPL-2
URL: https://myaseen208.com/bayesammi/,
        https://github.com/myaseen208/bayesammi
BugReports: https://github.com/myaseen208/bayesammi/issues
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.2)
Imports: coda, collapse, data.table, ggplot2, ggrepel, grDevices, MASS,
        Rcpp, scales, stats, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: bayesplot, bslib, DT, flextable, knitr, lme4, loo, magick,
        officer, pkgload, posterior, quarto, ragg, R.rsp, shiny,
        svglite, testthat (>= 3.0.0), withr
VignetteBuilder: quarto, R.rsp
Config/testthat/edition: 3
Config/skill/prefix: bam
RoxygenNote: 7.3.1
NeedsCompilation: yes
Packaged: 2026-11-10 02:44:51 UTC; myaseen208
Author: Muhammad Yaseen [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-5923-1714>),
  Jose Crossa [aut, ctb],
  Sergio Perez-Elizalde [aut, ctb],
  Diego Jarquin [aut, ctb],
  Jose Miguel Cotes [aut, ctb],
  Kert Viele [aut, ctb],
  Genzhou Liu [aut, ctb],
  Paul L. Cornelius [aut, ctb],
  Julian Garcia Abadillo Velasco [aut, ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Repository: CRAN
Date/Publication: 2026-11-10 09:30:23 UTC
