Multi Environment Trials Analysis
Description
Performs stability analysis of multi-environment
trial data using parametric and non-parametric methods. Parametric
methods includes Additive Main Effects and Multiplicative Interaction
(AMMI) analysis by Gauch (2013) ,
Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE)
biplot analysis by Yan & Kang (2003) ,
geometric adaptability index by Mohammadi & Amri (2008)
, joint regression analysis by Eberhart
& Russel (1966) ,
genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's
(2004) method , power law residuals
(POLAR) statistics by Doring et al. (2015)
, scale-adjusted coefficient of
variation by Doring & Reckling (2018) ,
stability variance by Shukla (1972) ,
weighted average of absolute scores by Olivoto et al. (2019a)
, and multi-trait stability index by
Olivoto et al. (2019b) .
Non-parametric methods includes superiority index by Lin & Binns
(1988) , nonparametric measures of phenotypic
stability by Huehn (1990)
, TOP third
statistic by Fox et al. (1990) . Functions for
computing biometrical analysis such as path analysis, canonical
correlation, partial correlation, clustering analysis, and tools for
inspecting, manipulating, summarizing and plotting typical
multi-environment trial data are also provided.