ammistability (version 0.1.2)

ASTAB.AMMI: AMMI Based Stability Parameter

Description

ASTAB.AMMI computes the AMMI Based Stability Parameter (ASTAB) rao_use_2005ammistability considering all significant interaction principal components (IPCs) in the AMMI model. Using ASTAB, the Simultaneous Selection Index for Yield and Stability (SSI) is also calculated according to the argument ssi.method.

Usage

ASTAB.AMMI(model, n, alpha = 0.05, ssi.method = c("farshadfar", "rao"), a = 1)

Arguments

model

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

n

The number of principal components to be considered for computation. The default value is the number of significant IPCs.

alpha

Type I error probability (Significance level) to be considered to identify the number of significant IPCs.

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:

ASTAB

The ASTAB values.

SSI

The computed values of simultaneous selection index for yield and stability.

rASTAB

The ranks of ASTAB 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 Based Stability Parameter value (ASTAB) rao_use_2005ammistability is computed as follows:

ASTAB = _n=1^N'_n_in^2

Where, N' is the number of significant IPCs (number of IPC that were retained in the AMMI model via F tests); _n is the singular value for nth IPC and correspondingly _n^2 is its eigen value; and _in is the eigenvector value for ith genotype.

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 n (N') and default ssi.method (farshadfar)
ASTAB.AMMI(model)

# With n = 4 and default ssi.method (farshadfar)
ASTAB.AMMI(model, n = 4)

# With default n (N') and ssi.method = "rao"
ASTAB.AMMI(model, ssi.method = "rao")

# Changing the ratio of weights for Rao's SSI
ASTAB.AMMI(model, ssi.method = "rao", a = 0.43)

# }