Predict the means of a performs_ammi object considering a specific number of axis.
An object of class performs_ammi
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
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 carefully chosen.
Procedures based on Postdictive success (such as Gollobs's d.f.) or
Predictive success (such as cross-validation) should be used to do this. This
package provide both.
performs_ammi() function compute
traditional AMMI analysis showing the number of significant axis. On the
cv_ammif() function provide a cross-validation,
estimating the RMSPD of all AMMI-family models, based on resampling
A list where each element is the predicted values by the AMMI model for each variable.
Tiago Olivoto firstname.lastname@example.org
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