ammistability (version 0.1.2)

MASV.AMMI: Modified AMMI Stability Value

Description

MASV.AMMI computes the Modified AMMI Stability Value (MASV) zali_evaluation_2012,ajay_rectification_2019ammistability (Please see Note) from a modified formula of AMMI Stability Value (ASV) purchase_parametric_1997ammistability. This formula calculates AMMI stability value considering all significant interaction principal components (IPCs) in the AMMI model. Using MASV, the Simultaneous Selection Index for Yield and Stability (SSI) is also calculated according to the argument ssi.method.

Usage

MASV.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:

MASV

The MASV values.

SSI

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

rMASV

The ranks of MASV 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 Modified AMMI Stability Value (MASV) ajay_rectification_2019ammistability is computed as follows:

MASV = _n=1^N'-1 (SSIPC_nSSIPC_n+1 PC_n )^2 + (PC_N' )^2

Where, SSIPC_1, SSIPC_2, , SSIPC_n are the sum of squares of the 1st, 2nd, ..., and nth IPC; and PC_1, PC_2, , PC_n are the scores of 1st, 2nd, ..., and nth IPC.

References

See Also

AMMI, index.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)
MASV.AMMI(model)

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

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

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

# }