Skip to contents

Compute BLUPS based on a set of mega environments

Source: R/createMegaEnv.R
predict.megaEnv.Rd

This function calculates Best Linear Unbiased Predictors (BLUPS) and associated standard errors based on a set of mega environments.

Usage

# S3 method for class 'megaEnv'
predict(
  object,
  ...,
  trials = names(object$TD),
  useYear = FALSE,
  engine = c("lme4", "asreml")
)

Arguments

object

An object of class megaEnv.

...

Further parameters passed to either asreml or lmer.

trials

A character string specifying the trials to be analyzed. If not supplied, all trials are used in the analysis.

useYear

Should year be used for modeling (as years within trials). If TRUE, TD should contain a column "year".

engine

A character string specifying the engine used for modeling.

Value

A list consisting of two data.frames, predictedValue containing BLUPs per genotype per mega environment and standardError containing standard errors for those BLUPs.

See also

Other mega environments: gxeMegaEnv(), plot.megaEnv()

Examples

## Compute mega environments for TDMaize.
geMegaEnv <- gxeMegaEnv(TD = TDMaize, trait = "yld")

## Compute BLUPS and standard errors for those mega environments.
megaEnvPred <- predict(geMegaEnv)
#> Warning: One should be cautious with the interpretation of predictions for mega environments that are based on less than 10 trials.
#> boundary (singular) fit: see help('isSingular')
head(megaEnvPred$predictedValue)
#>      megaEnv_1 megaEnv_2 megaEnv_3
#> G001  489.0515  483.5317  497.8785
#> G002  472.3096  491.5258  498.1123
#> G003  468.2102  457.0879  462.5265
#> G004  363.6653  361.1352  321.1292
#> G005  462.8374  465.0800  467.9159
#> G006  435.4026  419.0985  410.4387
head(megaEnvPred$standardError)
#>      megaEnv_1 megaEnv_2 megaEnv_3
#> G001  32.09261  38.36256  45.40008
#> G002  32.09261  38.36256  45.40008
#> G003  32.09261  38.36256  45.40008
#> G004  32.09261  38.36256  45.40008
#> G005  32.09261  38.36256  45.40008
#> G006  32.09261  38.36256  45.40008