Predictions are made based on the fitted model in the varComp object. These predictions can be at genotype level, at genotype x trial level or at the level of genotype x nestingFactor. If the model was fitted with trial as year x location then genotype x trial level becomes genotype x year x location.
Usage
# S3 method for class 'varComp'
predict(object, ..., predictLevel = "genotype")Arguments
- object
An object of class varComp.
- ...
Not used.
- predictLevel
A character string, the level at which prediction should be made. Either "genotype" for prediction at genotype level, "trial" for predictions at genotype x trial level, the variable used as nesting factor for predictions at the level of genotype x nestingFactor level, or one or more of the extra terms used in the model. E.g. c("region", "year") for a model fitted with
regionLocationYear = TRUE.
See also
Other Mixed model analysis:
CRDR(),
correlations(),
diagnostics(),
gxeVarComp(),
herit(),
plot.varComp(),
vc()
Examples
## Fit a mixed model.
geVarComp <- gxeVarComp(TD = TDMaize, trait = "yld")
## Predictions at genotype level.
predGeno <- predict(geVarComp)
head(predGeno)
#> genotype predictedValue
#> 1 G001 500.1561
#> 2 G002 479.8132
#> 3 G003 471.3800
#> 4 G004 346.9103
#> 5 G005 466.8594
#> 6 G006 425.9303
## Predictions at genotype x trial level.
predGenoTrial <- predict(geVarComp, predictLevel = "trial")
head(predGenoTrial)
#> genotype trial predictedValue
#> 1 G001 HN96b 529.1555
#> 2 G002 HN96b 508.8126
#> 3 G003 HN96b 500.3794
#> 4 G004 HN96b 375.9096
#> 5 G005 HN96b 495.8588
#> 6 G006 HN96b 454.9297