Access data on plant genetic resources from genebanks around the world published on Genesys (<https://www.genesys-pgr.org>).
Your use of data is subject to terms and conditions available at <https://www.genesys-pgr.org/content/legal/terms>.
c(person(family = "Global Crop Diversity Trust", role = c("cph")),
person("Matija", "Obreza", email = "matija.obreza@croptrust.org", role = c("aut", "cre")),
person("Nora", "Castaneda", email = "nora.castaneda@croptrust.org", role = c("ctb")))
Global Crop Diversity Trust [cph],
Matija Obreza [aut, cre],
Nora Castaneda [ctb]

Statistical Tools for the Analysis of Multi Environment
Agronomic Trials
c(
person(given = "Julia",
family = "Angelini",
role = c("aut", "cre"),
email = "jangelini_93@hotmail.com",
comment = c(ORCID = "0000-0002-9611-527X")
),
person(given = "Marcos",
family = "Prunello",
role = c("aut"),
email = "marcosprunello@gmail.com",
comment = c(ORCID = "0000-0002-9611-527X")
),
person(given = "Gerardo",
family = "Cervigni",
role = c("aut")
)
)
Data from multi environment agronomic trials, which are often
carried out by plant breeders, can be analyzed with the tools offered by this
package such as the Additive Main effects and Multiplicative Interaction model
or 'AMMI' ('Gauch' 1992, ISBN:9780444892409)
and the Site Regression model or 'SREG' ('Cornelius' 1996,
<doi:10.1201/9780367802226>). Since these methods present a poor performance
under the presence of outliers and missing values, this package includes
robust versions of the 'AMMI' model ('Rodrigues' 2016,
<doi:10.1093/bioinformatics/btv533>), and also imputation techniques
specifically developed for this kind of data ('Arciniegas-Alarcón' 2014,
<doi:10.2478/bile-2014-0006>).
stats, GGEBiplots, ggforce, ggplot2, scales, MASS, pcaMethods,
rrcov, dplyr, bcv, missMDA, calibrate, graphics, agridat,
reshape2, matrixStats, tidyr, prettydoc
Julia Angelini [aut, cre] (<https://orcid.org/0000-0002-9611-527X>),
Marcos Prunello [aut] (<https://orcid.org/0000-0002-9611-527X>),
Gerardo Cervigni [aut]