fixed effect constraint indication matrix
fcm creates a matrix with the correct number of columns to specify a constraint in the fixed effects using the Gtc argument of the vs function.
fcm(x, reps=NULL)
x |
vector of 1's and 0's corresponding to the traits for which this fixed effect should be fitted. For example, for a trivariate model if the fixed effect "x" wants to be fitted only for trait 1 and 2 but not for the 3rd trait then you would use fcm(c(1,1,0)) in the Gtc argument of the vs() function. |
reps |
integer specifying the number of times the matrix should be repeated in a list format to provide easily the constraints in complex models that use the ds(), us() or cs() structures. |
a matrix or a list of matrices with the constraints to be provided in the Gtc argument of the vs function.
Giovanny Covarrubias-Pazaran
Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744
fcm(c(1,1,0)) fcm(c(0,1,1)) fcm(c(1,1,1)) fcm(c(1,1,1),2) # ## model with Env estimated for both traits # data(DT_example) # DT <- DT_example # A <- A_example # ans4 <- mmer(cbind(Yield, Weight) ~ Env, # random= ~ vs(Name) + vs(Env:Name), # rcov= ~ vs(units), # data=DT) # summary(ans4)$betas # ## model with Env only estimated for Yield # ans4b <- mmer(cbind(Yield, Weight) ~ vs(Env, Gtc=fcm(c(1,0))), # random= ~ vs(Name) + vs(Env:Name), # rcov= ~ vs(units), # data=DT) # summary(ans4b)$betas
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