Description Usage Arguments Details Value Examples
The covariance matrix is set as maternal plus paternal LD matrix where the paternal part is a weighted average of sire-specific LD matrices.
1 | CovarMatrix(exp_freq_mat, LDDam, LDSire, Ns)
|
exp_freq_mat |
[MATRIX] paternal EXPECTATION matrix |
LDDam |
[MATRIX] maternal Linkage Disequilibrium matrix |
LDSire |
[LIST] Linkage disequilibrium matrices for the sires; each element of the list corresponds to a family |
Ns |
[VECTOR] family size for each sire s |
The internal suMM function works on lists!
covK
(p x p) matrix of covariance between markers
1 2 3 4 5 6 7 | data(testdata)
G <- Haplo2Geno(H.sire)
E <- ExpectMat(G)
LDfam2 <- LDsire(H.sire, pos.chr, family = 3:4)
LDfam3 <- LDsire(H.sire, pos.chr, family = 5:6)
## covariance matrix based on sires 2 and 3 only, each with 100 progeny
K <- CovarMatrix(E[2:3, ], LDDam = matLD, LDSire = list(LDfam2, LDfam3), Ns = c(100, 100))
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