Description Usage Arguments Details Author(s) Examples

View source: R/predict.WAAS.AMMI.R

Predict the means of a WAAS.AMMI object considering a specific number of axis.

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`object` |
An object of class WAAS.AMMI |

`naxis` |
The the number of axis to be use in the prediction. If |

`...` |
Additional parameter for the function |

This function is used to predict the response variable of a two-way table (for examples the yielding of the i-th genotype in the j-th environment) based on AMMI model. This prediction is based on the number of multiplicative terms used. If `naxis = 0`

, only the main effects (AMMI0) are used. In this case, the predicted mean will be the predicted value from OLS estimation. If `naxis = 1`

the AMMI1 (with one multiplicative term) is used for predicting the response variable. If `naxis = min(gen-1;env-1)`

, the AMMIF is fitted and the predicted value will be the cell mean, i.e. the mean of R-replicates of the i-th genotype in the j-th environment. The number of axis to be used must be carrefully chosen. Precures based on Postdictive sucess (such as Gollobs's d.f.) or Predictive sucess (such as cross-validation) should be used to do this. This package provide both. `WAAS.AMMI`

function compute traditional AMMI analysis showing the number of significant axis. On the other hand, `validation.AMMIF`

function provide a cross-validation, estimating the RMSE of all AMMI-family models, based on resampling procedure.

Tiago Olivoto [email protected]

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