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) , 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) < https://link.springer.com/article/10.1007/BF00024241>, 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.


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install.packages("metan")

1.9.0 by Tiago Olivoto, 12 days ago


https://github.com/TiagoOlivoto/metan


Report a bug at https://github.com/TiagoOlivoto/metan/issues


Browse source code at https://github.com/cran/metan


Authors: Tiago Olivoto [aut, cre, cph]


Documentation:   PDF Manual  


GPL-3 license


Imports cowplot, dplyr, GGally, ggforce, ggplot2, ggrepel, grid, lme4, lmerTest, magrittr, mathjaxr, methods, progress, purrr, rlang, tibble, tidyr, tidyselect

Suggests DT, knitr, rmarkdown, roxygen2


See at CRAN