Description Usage Arguments Details Value Author(s) References
contLikMLE optimizes the likelihood of the STR DNA mixture given some assumed a bayesian model.
1 2 3 4 |
nC |
Number of contributors in model. |
samples |
A List with samples which for each samples has locus-list elements with list elements adata and hdata. 'adata' is a qualitative (allele) data vector and 'hdata' is a quantitative (peak heights) data vector. |
popFreq |
A list of allele frequencies for a given population. |
refData |
Reference objects with (2-size) allele-vector given in list element [[i]][[s]]. |
condOrder |
Specify conditioning references from refData (must be consistent order). For instance condOrder=(0,2,1,0) means that we restrict the model such that Ref2 and Ref3 are respectively conditioned as 2. contributor and 1. contributor in the model. |
knownRef |
Specify known non-contributing references from refData (index). For instance knownRef=(1,2) means that reference 1 and 2 is known non-contributor in the hypothesis. This affectes coancestry correction. |
xi |
A numeric giving stutter-ratio if it is known. Default is NULL, meaning it is integrated out. |
prC |
A numeric for allele drop-in probability. Default is 0. |
nDone |
Maximum number of random evaluations nlm-optimizing routing. Default is 1. |
threshT |
The detection threshold given. Used when considering probability of allele drop-outs. |
fst |
The co-ancestry coefficient. Default is 0. |
lambda |
Parameter in modeled peak height shifted exponential model. Default is 0. |
pXi |
Prior function for xi-parameter (stutter). Flat prior on [0,1] is default. |
delta |
Standard deviation of normal distribution when drawing random startpoints. Default is 10. |
kit |
Used to model degradation. Must be one of the shortnames of kit: "ESX17","ESI17","ESI17Fast","ESX17Fast","Y23","Identifiler","NGM","ESSPlex","ESSplexSE","NGMSElect","SGMPlus","ESX16", "Fusion","GlobalFiler". |
verbose |
Boolean whether printing optimization progress. Default is TRUE. |
The procedure are doing numerical optimization to approximate the marginal probabilit over noisance parameters. Mixture proportions have flat prior.
The procedure also does a Laplace Approximation of the marginalized likelihood (theta integrated out) and returns the log-marginal likelihood as logmargL in the fit-list.
Function calls procedure in c++ by using the package Armadillo and Boost.
ret A list(fit,model,nDone,delta) where fit is Maximixed likelihood elements for given model.
Oyvind Bleka <Oyvind.Bleka.at.fhi.no>
Cowell,R.G. et.al. (2014). Analysis of forensic DNA mixtures with artefacts. Applied Statistics, 64(1),1-32.
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