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) doi:10.2135/cropsci2013.04.0241, Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) doi:10.1201/9781420040371, geometric adaptability index by Mohammadi & Amri (2008) doi:10.1007/s10681-007-9600-6, joint regression analysis by Eberhart & Russel (1966) doi:10.2135/cropsci1966.0011183X000600010011x, genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method, power law residuals (POLAR) statistics by Doring et al. (2015) doi:10.1016/j.fcr.2015.08.005, scale-adjusted coefficient of variation by Doring & Reckling (2018) doi:10.1016/j.eja.2018.06.007, stability variance by Shukla (1972) doi:10.1038/hdy.1972.87, weighted average of absolute scores by Olivoto et al. (2019a) doi:10.2134/agronj2019.03.0220, and multi-trait stability index by Olivoto et al. (2019b) doi:10.2134/agronj2019.03.0221. Non-parametric methods includes superiority index by Lin & Binns (1988) doi:10.4141/cjps88-018, nonparametric measures of phenotypic stability by Huehn (1990) , TOP third statistic by Fox et al. (1990) doi:10.1007/BF00040364. 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.
Citation | metan citation info |
github.com/TiagoOlivoto/metan | |
Bug report | File report |