SIPC.AMMI {ammistability} | R Documentation |

`SIPC.AMMI`

computes the Sums of the Absolute Value of the IPC Scores
(ASI) (Sneller et al. 1997) considering all
significant interaction principal components (IPCs) in the AMMI model. Using
SIPC, the Simultaneous Selection Index for Yield and Stability (SSI) is also
calculated according to the argument `ssi.method`

.

SIPC.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 Sums of the Absolute Value of the IPC Scores (\(SIPC\)) (Sneller et al. 1997) is computed as follows:

\[SIPC = \sum_{n=1}^{N'} \left | \lambda_{n}^{0.5}\gamma_{in} \right |\]OR

\[SIPC = \sum_{n=1}^{N'}\left | PC_{n} \right |\]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; \(\gamma_{in}\) is the eigenvector value for \(i\)th genotype; and \(PC_{1}\), \(PC_{2}\), \(\cdots\), \(PC_{n}\) are the scores of 1st, 2nd, ..., and \(n\)th IPC.

The closer the SIPC scores are to zero, the more stable the genotypes are across test environments.

A data frame with the following columns:

`SIPC` |
The SIPC values. |

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

`rSIPC` |
The ranks of SIPC 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.

Sneller CH, Kilgore-Norquest L, Dombek D (1997).
“Repeatability of yield stability statistics in soybean.”
*Crop Science*, **37**(2), 383–390.
doi: 10.2135/cropsci1997.0011183X003700020013x, https://doi.org/10.2135/cropsci1997.0011183X003700020013x.

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

[Package *ammistability* version 0.1.2 Index]