weight.famdep {LCAextend} | R Documentation |
performs the computation of triplet and individual weights for a pedigree under familial dependence
Description
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 log-likelihood of the observations. This is an internal function not meant to be called by the user.
Usage
weight.famdep(id, dad, mom, status, probs, fyc, peel)
Arguments
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 |
Details
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.
Value
the function returns a list of 3 elements:
ww |
triplet weights: an array of |
w |
individual weights: an array of |
ll |
log-likelihood. |
References
TAYEB et al.: Solving Genetic Heterogeneity in Extended Families by Identifying Sub-types of Complex Diseases. Computational Statistics, 2011, DOI: 10.1007/s00180-010-0224-2.
See Also
See also upward
, downward
, e.step
.
Examples
#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)