computes the triplet and the individual weights of the E step of the EM algorithm for a pedigree in the case of familial dependence. It returns also the overall loglikelihood of the observations. This is an internal function not meant to be called by the user.
1  weight.famdep(id, dad, mom, status, probs, fyc, peel)

id 
individual ID of the pedigree, 
dad 
dad ID, 
mom 
mom ID, 
status 
symptom status: (2: symptomatic, 1: without symptoms, 0: missing), 
probs 
list of probability parameters of the model, 
fyc 
a matrix of 
peel 
a list of pedigree peeling containing connectors by peeling order and couples of parents 
the function calls the functions upward
and
downward
which perform the required probability
computations by processing the pedigree by nuclear family (or
equivalently by connector) following the peeling order.
the function returns a list of 3 elements:
ww 
triplet weights: an array of 
w 
individual weights: an array of 
ll 
loglikelihood. 
TAYEB et al.: Solving Genetic Heterogeneity in Extended Families by Identifying Subtypes of Complex Diseases. Computational Statistics, 2011, DOI: 10.1007/s0018001002242.
See also upward
, downward
, e.step
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19  #data
data(ped.cont)
data(peel)
fam < ped.cont[,1]
id < ped.cont[fam==1,2]
dad < ped.cont[fam==1,3]
mom < ped.cont[fam==1,4]
status < ped.cont[fam==1,6]
y < ped.cont[fam==1,7:ncol(ped.cont)]
peel < peel[[1]]
#probs and param
data(probs)
data(param.cont)
#densities of the observations
fyc < matrix(1,nrow=length(id),ncol=length(probs$p)+1)
fyc[status==2,1:length(probs$p)] < t(apply(y[status==2,],1,dens.norm,
param.cont,NULL))
#the function
weight.famdep(id,dad,mom,status,probs,fyc,peel)

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