ASI.AMMI | R Documentation |
ASI.AMMI
computes the AMMI Stability Index (ASI)
\insertCitejambhulkar_ammi_2014,jambhulkar_genotype_2015,jambhulkar_stability_2017ammistability
considering the first two interaction principal components (IPCs) in the AMMI
model. Using ASI, the Simultaneous Selection Index for Yield and Stability
(SSI) is also calculated according to the argument ssi.method
.
\loadmathjax
ASI.AMMI(model, ssi.method = c("farshadfar", "rao"), a = 1)
model |
The AMMI model (An object of class |
ssi.method |
The method for the computation of simultaneous selection
index. Either |
a |
The ratio of the weights given to the stability components for
computation of SSI when |
The AMMI Stability Index (\mjseqnASI) \insertCitejambhulkar_ammi_2014,jambhulkar_genotype_2015,jambhulkar_stability_2017ammistability is computed as follows:
\mjsdeqnASI = \sqrt\left [ PC_1^2 \times \theta_1^2 \right ]+\left [ PC_2^2 \times \theta_2^2 \right ]
Where, \mjseqnPC_1 and \mjseqnPC_2 are the scores of 1st and 2nd IPCs respectively; and \mjseqn\theta_1 and \mjseqn\theta_2 are percentage sum of squares explained by the 1st and 2nd principal component interaction effect respectively.
A data frame with the following columns:
ASI |
The ASI values. |
SSI |
The computed values of simultaneous selection index for yield and stability. |
rASI |
The ranks of ASI values. |
rY |
The ranks of the mean yield of genotypes. |
means |
The mean yield of the genotypes. |
The names of the genotypes are indicated as the row names of the data frame.
AMMI
, SSI
library(agricolae)
data(plrv)
# AMMI model
model <- with(plrv, AMMI(Locality, Genotype, Rep, Yield, console = FALSE))
# ANOVA
model$ANOVA
# IPC F test
model$analysis
# Mean yield and IPC scores
model$biplot
# G*E matrix (deviations from mean)
array(model$genXenv, dim(model$genXenv), dimnames(model$genXenv))
# With default ssi.method (farshadfar)
ASI.AMMI(model)
# With ssi.method = "rao"
ASI.AMMI(model, ssi.method = "rao")
# Changing the ratio of weights for Rao's SSI
ASI.AMMI(model, ssi.method = "rao", a = 0.43)
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