likestim.loc {forensim} | R Documentation |
The likestim.loc
function returns the estimation of the number of contributors,
at each locus, obtained by maximizing the likelihood.
likestim.loc(mix, freq, refpop = NULL, theta = NULL, loc = NULL)
mix |
a simumix object |
freq |
a tabfreq object containing the allele frequencies to use for the calculation |
refpop |
the reference population from which to extract the allele frequencies used in the likelihood
calculation. Default set to NULL, if tabfreq contains more than one population, refpop must be
specified |
theta |
a float from [0,1[ giving Wright's Fst coefficient. theta acounts for population subdivision while
computing the likelihood of the data. |
loc |
loci to be considered in the estimation. Default (set to NULL) corresponds to all loci. |
The number of contributors which maximizes the likelihood of the data observed in the mixture is searched in the discrete interval [1,6]. In most cases this interval is a plausible range for the number of contributors.
A matrix of dimension loc
x 2. The first colum, max
, gives the maximum likelihood estimation
of the number of contributors for each locus in row. The second column, maxvalue
,
gives the corresponding likelihood value.
Hinda Haned <haned@biomserv.univ-lyon1.fr>
Haned H, Pontier D, Lobry JR, Pene L, Dufour AB.
Estimating the number of contributors to forensic DNA mixtures: Does maximum likelihood
perform better than maximum allele count? Submitted, 2009.
Egeland T , Dalen I, Mostad PF.
Estimating the number of contributors to a DNA profile. Int J Legal Med 2003, 117: 271-275
Curran, JM , Triggs CM, Buckleton J , Weir BS. Interpreting DNA Mixtures in Structured Populations. J Forensic Sci 1999, 44(5): 987-995
likestim
for multiloci estimations
data(strusa) #simulation of 1000 genotypes from the Hispanic allele frequencies gen<-simugeno(strusa,n=c(0,0,100)) #4-person mixture mix4 <- simumix(gen,ncontri=c(0,0,4)) likestim.loc(mix4,strusa,refpop="Hisp")