predict.waas  R Documentation 
Predict the means of a waas object considering a specific number of axis.
## S3 method for class 'waas' predict(object, naxis = 2, ...)
object 
An object of class waas 
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 twoway table
(for examples the yielding of the ith genotype in the jth 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(gen1;env1)
, the AMMIF is fitted and the predicted value will be the
cell mean, i.e. the mean of Rreplicates of the ith genotype in the jth
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 sucess (such as crossvalidation) should be used to do this. This
package provide both. waas()
function compute traditional AMMI
analysis showing the number of significant axis. On the other hand,
cv_ammif()
function provide a crossvalidation, estimating the
RMSPD of all AMMIfamily models, based on resampling procedures.
A list where each element is the predicted values by the AMMI model for each variable.
Tiago Olivoto tiagoolivoto@gmail.com
library(metan) model < waas(data_ge, env = ENV, gen = GEN, rep = REP, resp = c(GY, HM)) # Predict GY with 3 IPCA and HM with 1 IPCA predict < predict(model, naxis = c(3, 1)) predict
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