data(DT_btdata)
DT <- DT_btdata
head(DT)
# \donttest{
mix4 <- lmebreed(tarsus ~ sex + (1|dam) + (1|fosternest),
# how to control n iterations
# control = lmerControl(
# optCtrl = list(maxfun = 100, maxeval = 100)
# ),
data = DT)
vc <- VarCorr(mix4); print(vc,comp=c("Variance"))
sigma(mix4)^2 # error variance
BLUP <- ranef(mix4, condVar=TRUE)
SEs <- attr(BLUP$dam, which="postVar")[,,]
### multi-trait model
traits <- c("tarsus" ,"back", "hatchdate")
for(iTrait in traits){DT[,iTrait] <- scale(DT[,iTrait])}
DTL <- reshape(DT[,c("animal", traits)], idvar = "animal", varying = traits,
v.names = "value", direction = "long",
timevar = "trait", times = traits )
DTL <- merge(DTL, unique(DT[,c("animal","dam","fosternest","sex")]),
by="animal", all.x = TRUE)
DTL <- DTL[with(DTL, order(trait)), ]
head(DTL)
system.time(
mix <- lmebreed(value ~ (0+trait|dam),
# relmat = list(geno=A),
# rotation = TRUE,
data=DTL)
)
vc <- VarCorr(mix); print(vc,comp=c("Variance"))
cov2cor(vc$dam)
sigma(mix)^2 # error variance
# }
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