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covaruber avatar covaruber commented on May 26, 2024

Hello Julia, indeed now fitted only provide y=Xb different than before. Currently the best way to obtain the fitted values using all the random effects (Xb+Zu) is to use the predict() function available in sommer. See for example:

data(DT_cornhybrids)
DT_cornhybrids <- DT

hybrid2 <- DT # extract cross data
A <- GT
K1 <- A[levels(hybrid2$GCA1), levels(hybrid2$GCA1)]; dim(K1)
K2 <- A[levels(hybrid2$GCA2), levels(hybrid2$GCA2)]; dim(K2)
S <- kronecker(K1, K2) ; dim(S)
rownames(S) <- colnames(S) <- levels(hybrid2$SCA)

ans <- mmer(Yield ~ Location,
             random = ~ vs(GCA1,Gu=K1) + vs(GCA2,Gu=K2) + vs(SCA,Gu=S),
             rcov=~units,
             data=hybrid2)
pp <- predict(ans)
head(pp$fitted) # has all fixed and random effects added

I hope this helps. Cheers!

from sommer.

jpiaskowski avatar jpiaskowski commented on May 26, 2024

Thank you, will do.

from sommer.

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