Fit linear or generalized linear mixed models incorporating the effects of a pedigree.
1 2 3 4 5 
pedigree 
a named list of 
formula 
as in 
data 
as in 
family 
as in 
REML 
as in 
control 
as in 
start 
as in 
verbose 
as in 
subset 
as in 
weights 
as in 
na.action 
as in 
offset 
as in 
contrasts 
as in 
model 
as in 
x 
as in 
... 
as in 
All arguments to this function are the same as those to the function
lmer
except pedigree
which must be a named list of
pedigree
objects. Each name (frequently there is
only one) must correspond to the name of a grouping factor in a
randomeffects term in the formula
. The observed levels
of that factor must be contained in the pedigree. For each pedigree
the (left) Cholesky factor of the
relationship matrix restricted to the observed levels is calculated
using relfactor
and applied to the model matrix for that
term.
a pedigreemm
object.
2010. A.I. Vazquez, D.M. Bates, G.J.M. Rosa, D. Gianola and K.A. Weigel. Technical Note: An R package for fitting generalized linear mixed models in animal breeding. Journal of Animal Science, 88:497504.
pedigreemm
, pedigree
,
relfactor
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  p1 < new("pedigree",
sire = as.integer(c(NA,NA,1, 1,4,5)),
dam = as.integer(c(NA,NA,2,NA,3,2)),
label = as.character(1:6))
A<getA(p1)
cholA<chol(A)
varU<0.4; varE<0.6; rep<20
n<rep*6
set.seed(108)
bStar< rnorm(6, sd=sqrt(varU))
b<crossprod(as.matrix(cholA),bStar)
ID < rep(1:6, each=rep)
e0<rnorm(n, sd=sqrt(varE))
y<b[ID]+e0
fm1 < pedigreemm(y ~ (1ID) , pedigree = list(ID = p1))
table(y01<ifelse(y<1.3,0,1))
fm2 < pedigreemm(y01 ~ (1ID) , pedigree = list(ID = p1), family = 'binomial')

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