Multi Environment Trials Analysis

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) , Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) , joint Regression Analysis by Eberhart & Russel (1966) (), ecovalence by Wricke (1965), genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method , 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) < https://link.springer.com/article/10.1007/BF00024241>, TOP third statistic by Fox et al. (1990) , geometric adaptability index described by Shahbazi (2019) . 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.


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