WGabriel: Weighted GabrielEigen imputation method
In geneticae: Statistical Tools for the Analysis of Multi Environment Agronomic Trials
View source: R/W_GabrielEigen.R
WGabriel R Documentation
Weighted GabrielEigen imputation method
Description
agregar descripcion.
Usage
WGabriel(DBmiss, Winf, Wsup)
Arguments
DBmiss
a data frame or matrix that contains the genotypes in the rows
and the environments in the columns when there are no replications of the
experiment.
Winf
inferior weight
Wsup
superior weight
Value
A list containing:
Peso: weight that provides the best predictive difference;
NumeroIterWGabriel: the final number of iterations;
CritConvergWGabriel: the maximum change of the estimated
values for missing cells in the last step of iteration (the precision of
convergence);
GabrielWImput: the imputed matrix (filled in with the
missing values estimated by the Weighted GabrielEigen procedure).
References
Arciniegas-Alarcón S., García-Peña M., Krzanowski W.J., Dias
C.T.S. (2014). An alternative methodology for imputing missing data in
trials with genotype-byenvironment interaction: some new aspects.
Biometrical Letters 51, 75-88.
geneticae documentation built on July 20, 2022, 5:06 p.m.
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View source: R/W_GabrielEigen.R
| WGabriel | R Documentation |
Weighted GabrielEigen imputation method
Description
agregar descripcion.
Usage
WGabriel(DBmiss, Winf, Wsup)
Arguments
DBmiss |
a data frame or matrix that contains the genotypes in the rows and the environments in the columns when there are no replications of the experiment. |
Winf |
inferior weight |
Wsup |
superior weight |
Value
A list containing:
Peso: weight that provides the best predictive difference;
NumeroIterWGabriel: the final number of iterations;
CritConvergWGabriel: the maximum change of the estimated values for missing cells in the last step of iteration (the precision of convergence);
GabrielWImput: the imputed matrix (filled in with the missing values estimated by the Weighted GabrielEigen procedure).
References
Arciniegas-Alarcón S., García-Peña M., Krzanowski W.J., Dias C.T.S. (2014). An alternative methodology for imputing missing data in trials with genotype-byenvironment interaction: some new aspects. Biometrical Letters 51, 75-88.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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