fai_blup | R Documentation |
Multitrait index based on factor analysis and ideotype-design proposed by Rocha et al. (2018).
fai_blup( .data, use_data = "blup", DI = NULL, UI = NULL, SI = 15, mineval = 1, verbose = TRUE )
.data |
An object of class |
use_data |
Define which data to use If |
DI, UI |
A vector of the same length of |
SI |
An integer (0-100). The selection intensity in percentage of the total number of genotypes. Defaults to 15. |
mineval |
The minimum value so that an eigenvector is retained in the factor analysis. |
verbose |
Logical value. If |
An object of class fai_blup
with the following items:
data The data (BLUPS) used to compute the index.
eigen The eigenvalues and explained variance for each axis.
FA The results of the factor analysis.
canonical_loadings The canonical loadings for each factor retained.
FAI A list with the FAI-BLUP index for each ideotype design.
sel_dif_trait A list with the selection differential for each ideotype design.
sel_gen The selected genotypes.
ideotype_construction A list with the construction of the ideotypes.
total_gain A list with the total gain for variables to be increased or decreased.
Tiago Olivoto tiagoolivoto@gmail.com
Rocha, J.R.A.S.C.R, J.C. Machado, and P.C.S. Carneiro. 2018. Multitrait index based on factor analysis and ideotype-design: proposal and application on elephant grass breeding for bioenergy. GCB Bioenergy 10:52-60. doi: 10.1111/gcbb.12443
library(metan) mod <- waasb(data_ge, env = ENV, gen = GEN, rep = REP, resp = c(GY, HM)) FAI <- fai_blup(mod, SI = 15, DI = c('max, max'), UI = c('min, min'))
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