Description Usage Arguments Details Value References See Also Examples

`DA.AMMI`

computes the Annicchiarico's D Parameter values
(D_{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
D_{a}, the
Simultaneous Selection Index for Yield and Stability (SSI) is also calculated
according to the argument `ssi.method`

.

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}*) is computed as
follows:

*D _{a}
=√[∑^{N'}_{n=1}
(λ_{n}γ_{in})^{2}]*

Where, *N'* is the number of significant
IPCs (number of IPC that were retained in the AMMI model via F tests);
*λ _{n}* is the
singular value for

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_joint_1997ammistability

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | ```
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)
``` |

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