Matrix of alleles, such that each locus has a pair of
adjacent columns of alleles, and the order of columns
corresponds to the order of loci on a chromosome. If
there are K loci, then ncol(data) = 2*K. Rows represent
alleles fo
locus.label
Vector of labels for loci, of length K (see definition of data matrix).
converge.eps
Convergence criterion, based on absolute change in log likelihood (lnlike).
maxiter
Maximum number of iterations of EM
miss.val
missing value
Value
List with components:
convergeIndicator of convergence of the EM algorithm
(1=converged, 0 = failed).
niterNumber of iterations completed in the EM alogrithm.
locus.infoA list with a component for each locus. Each
component is also a list, and the items of a locus-
specific list are the locus name and a vector for the
unique alleles for the locus.
locus.labelVector of labels for loci, of length K (see
definition of input values).
haplotypeMatrix of unique haplotypes. Each row represents a
unique haplotype, and the number of columns is the number of loci.
hap.probVector of mle's of haplotype probabilities. The ith
element of hap.prob corresponds to the ith row of haplotype.
lnlikeValue of lnlike at last EM iteration (maximum lnlike if converged).
indx.subjVector for index of subjects, after expanding to
all possible pairs of haplotypes for each person. If
indx=i, then i is the ith row of input matrix data. If the
ith subject has n possible pairs of haplotypes that
correspond to their marker phenotype, then i is repeated n times.
nrepsVector for the count of haplotype pairs that map to
each subject's marker genotypes.
hap1codeVector of codes for each subject's first haplotype.
The values in hap1code are the row numbers of the unique
haplotypes in the returned matrix haplotype.
hap2codeSimilar to hap1code, but for each subject's second haplotype.
postVector of posterior probabilities of pairs of
haplotypes for a person, given thier marker phenotypes.