BGGE: Bayesian Genomic Linear Models Applied to GE Genome Selection
Application of genome prediction for a continuous variable, focused 
             on genotype by environment (GE) genomic selection models (GS). It consists a group of functions 
             that help to create regression kernels for some GE genomic models proposed by Jarquín et al. (2014) <doi:10.1007/s00122-013-2243-1>
             and Lopez-Cruz et al. (2015) <doi:10.1534/g3.114.016097>. Also, it computes genomic predictions based on Bayesian approaches.
             The prediction function uses an orthogonal transformation of the data and specific priors
             present by Cuevas et al. (2014) <doi:10.1534/g3.114.013094>.
| Version: | 
0.6.5 | 
| Depends: | 
R (≥ 3.1.1) | 
| Imports: | 
stats | 
| Suggests: | 
BGLR, coda | 
| Published: | 
2018-08-10 | 
| DOI: | 
10.32614/CRAN.package.BGGE | 
| Author: | 
Italo Granato [aut, cre],
  Luna-Vázquez Francisco J. [aut],
  Cuevas Jaime [aut] | 
| Maintainer: | 
Italo Granato  <italo.granato at gmail.com> | 
| License: | 
GPL-3 | 
| NeedsCompilation: | 
no | 
| Materials: | 
NEWS  | 
| In views: | 
Agriculture | 
| CRAN checks: | 
BGGE results | 
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