DA.AMMI {ammistability} | R Documentation |

`DA.AMMI`

computes the Annicchiarico's D Parameter values
(\(\textrm{D}_{\textrm{a}}\))
(Annicchiarico 1997) considering all
significant interaction principal components (IPCs) in the AMMI model. It is
the unsquared Euclidean distance from the origin of significant IPC axes in
the AMMI model. Using \(\textrm{D}_{\textrm{a}}\), the Simultaneous
Selection Index for Yield and Stability (SSI) is also calculated according to
the argument `ssi.method`

.

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

`model` |
The AMMI model (An object of class |

`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 |

`a` |
The ratio of the weights given to the stability components for
computation of SSI when |

The Annicchiarico's D Parameter value (\(D_{a}\)) (Annicchiarico 1997) is computed as follows:

\[D_{a} = \sqrt{\sum_{n=1}^{N'}(\lambda_{n}\gamma_{in})^2}\]Where, \(N'\) is the number of significant IPCs (number of IPC that were retained in the AMMI model via F tests); \(\lambda_{n}\) is the singular value for \(n\)th IPC and correspondingly \(\lambda_{n}^{2}\) is its eigen value; and \(\gamma_{in}\) is the eigenvector value for \(i\)th genotype.

A data frame with the following columns:

`DA` |
The DA values. |

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

`rDA` |
The ranks of DA 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.

Annicchiarico P (1997).
“Joint regression vs AMMI analysis of genotype-environment interactions for cereals in Italy.”
*Euphytica*, **94**(1), 53–62.
doi: 10.1023/A:1002954824178, https://link.springer.com/article/10.1023/A:1002954824178.

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) DA.AMMI(model) # With n = 4 and default ssi.method (farshadfar) DA.AMMI(model, n = 4) # With default n (N') and ssi.method = "rao" DA.AMMI(model, ssi.method = "rao") # Changing the ratio of weights for Rao's SSI DA.AMMI(model, ssi.method = "rao", a = 0.43)

[Package *ammistability* version 0.1.2 Index]