## Not run: ------------------------------------
# library(synbreedData)
# data(maize)
# maizeC <- codeGeno(maize)
#
# # pedigree-based (expected) kinship matrix
# K <- kin(maizeC,ret="kin",DH=maize$covar$DH)
#
# # marker-based (realized) relationship matrix
# # divide by an additional factor 2
# # because for testcross prediction the kinship of DH lines is used
# U <- kin(maizeC,ret="realized")/2
# # BLUP models
# # P-BLUP
# mod1 <- gpMod(maizeC,model="BLUP",kin=K)
# # G-BLUP
# mod2 <- gpMod(maizeC,model="BLUP",kin=U)
#
# # Bayesian Lasso
# prior <- list(varE=list(df=3,S=35),lambda = list(shape=0.52,rate=1e-4,value=20,type='random'))
# mod3 <- gpMod(maizeC,model="BL",prior=prior,nIter=6000,burnIn=1000,thin=5)
#
# summary(mod1)
# summary(mod2)
# summary(mod3)
## ---------------------------------------------
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