This function is for development purposes. It returns, as "predictions", an array of
random numbers. It accept the standard inputs and produces a formally correct output. It
is, obviously, quite fast.
The function should return a list with the following fields:
predictions : an array of (k) predicted phenotypes
hyperparams : named array of hyperparameters selected during training
extradata : any extra information
Arguments
phenotypes
phenotypes, numeric array (n x 1), missing values are predicted
genotypes
SNP genotypes, one row per phenotype (n), one column per marker (m), values in 0/1/2 for
diploids or 0/1/2/...ploidy for polyploids. Can be NULL if covariances is present.
covariances
square matrix (n x n) of covariances. Can be NULL if genotypes is present.
extraCovariates
extra covariates set, one row per phenotype (n), one column per covariate (w).
If NULL no extra covariates are considered.
See Also
Other phenoRegressors:
phenoRegressor.BGLR(),
phenoRegressor.RFR(),
phenoRegressor.SVR(),
phenoRegressor.rrBLUP(),
phenoregressor.BGLR.multikinships()
#genotypes are not really investigated. Only#number of test phenotypes is used.phenoRegressor.dummy(
phenotypes = c(1:10, NA, NA, NA),
genotypes = matrix(nrow = 13, ncol=30)
)