lik: Likelihood of the observed alleles at different loci in a DNA...
In forensim: Statistical tools for the interpretation of forensic DNA mixtures

Description Usage Arguments Details Author(s) References See Also Examples

The lik function computes the likelihood of the observed alleles in a forensic DNA mixture, for a set of loci, conditional on the number of contributors to the mixture. The overall likelihood is computed as the product of loci likelihoods.

1	lik(x = 1, mix, freq, refpop = NULL, theta = NULL, loc=NULL)

`x`	the number of contributors to the DNA mixture, default is 1
`mix`	a `simumix` object which contains the mixture to be analyzed
`freq`	a `tabfreq` object from which to extract the allele frequencies
`refpop`	a factor giving the reference population in `tabfreq` from which to extract the allele frequencies. This argument is used only if `freq` contains allele frequencies for multiple populations, otherwise it is by default set to NULL
`theta`	a float from [0,1[ giving Wright's Fst coefficient. `theta` accounts for population subdivision while computing the likelihood of the data
`loc`	loci for which the overall likelihood shall be computed. Default (NULL) corresponds to all loci

lik computes the likelihood of the alleles observed at all loci conditional on the number of contributors. This function implements the general formula for the interpretation of DNA mixtures in case of population subdivision (Curran et al, 1999), in the particular case where all contributors are unknown and belong to the same subpopulation.
The likelihood for multiple loci is computed as the product of loci likelihoods.

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): 987-995

lik.loc for the likelihood per locus, likestim and likestim.loc for the estimation of the number of contributors to a DNA mixture through likelihood maximization

data(strusa)
#simulation of 1000 genotypes from the African American allele frequencies
gen<-simugeno(strusa,n=c(1000,0,0))
#3-person mixture
mix3<-simumix(gen,ncontri=c(3,0,0))
sapply(1:3, function(i) lik(x=i,mix3, strusa, refpop="Afri"))