ammistability (version 0.1.2)

ASI.AMMI: AMMI Stability Index

Description

ASI.AMMI computes the AMMI Stability Index (ASI) jambhulkar_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.

Usage

ASI.AMMI(model, ssi.method = c("farshadfar", "rao"), a = 1)

Arguments

model

The AMMI model (An object of class AMMI generated by AMMI).

ssi.method

The method for the computation of simultaneous selection index. Either "farshadfar" or "rao" (See SSI).

a

The ratio of the weights given to the stability components for computation of SSI when method = "rao" (See SSI).

Value

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.

Details

The AMMI Stability Index (ASI) jambhulkar_ammi_2014,jambhulkar_genotype_2015,jambhulkar_stability_2017ammistability is computed as follows:

ASI = [ PC_1^2 _1^2 ]+ [ PC_2^2 _2^2 ]

Where, PC_1 and PC_2 are the scores of 1st and 2nd IPCs respectively; and _1 and _2 are percentage sum of squares explained by the 1st and 2nd principal component interaction effect respectively.

References

See Also

AMMI, SSI

Examples

# NOT RUN {
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)

# }