The lik.loc
function computes the likelihood of the observed data in a forensic DNA mixture, for each of the loci involved, conditional on the number of contributors to
the mixture.
1 
x 
the number of contributors to the DNA mixture 
mix 
a 
freq 
a 
refpop 
a factor giving the reference population in 
theta 
a float from [0,1[ giving Wright's Fst coefficien. 
loc 
the loci for which the likelihood shall be computed. Default (set to NULL) corresponds to all loci. 
lik.loc
computes the likelihood per locus of the observed alleles.
This function implements the general formula for the interpretation
of DNA mixtures in case of subdivided populations (Curran et al, 1999), in the particular case where all contributors
are unknown and belong to the same subpopulation.
The Fst coefficient given in the theta
argument allows accounting for population subdivision when all
contributors belong to the same subpopulation.
The function lik.loc
returns a vector, of length the number of loci in loc
,
giving the likelihood of the data for each locus.
Hinda Haned <contact@hindahaned.info>
Haned H, Pene L, Lobry JR, Dufour AB, Pontier D.
Estimating the number of contributors to forensic DNA mixtures: Does maximum likelihood
perform better than maximum allele count? J Forensic Sci, accepted 2010.
Curran JM, Triggs CM, Buckleton J, Weir BS. Interpreting DNA Mixtures in Structured Populations. J Forensic Sci 1999;44(5): 987995
lik
for the overall loci likelihood, likestim
and
likestim.loc
for the estimation of the number of contributors to a DNA mixture through
likelihood maximization
1 2 3 4 5 6 7 8 9 10  data(strusa)
#simulation of 1000 genotypes from the Caucasian allele frequencies
gen<simugeno(strusa,n=c(0,100,0))
#4person mixture
mix4 < simumix(gen,ncontri=c(0,4,0))
lik.loc(x=2,mix4, strusa, refpop="Cauc")
lik.loc(x=2,mix4, strusa, refpop="Afri")
#You may also want to try:
#likestim(mix4,strusa,refpop="Cauc")

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