contLikMLE: contLikMLE
In gammadnamix: Package for intepretation of quantitative DNA mixtures

Description Usage Arguments Details Value Author(s) References

contLikMLE optimizes the likelihood of the STR DNA mixture given some assumed a bayesian model.

contLikMLE(nC, samples, popFreq, refData = NULL, condOrder = NULL,
  knownRef = NULL, xi = NULL, prC = 0, nDone = 1, threshT = 50,
  fst = 0, lambda = 0, pXi = function(x) 1, delta = 10, kit = NULL,
  verbose = TRUE)

`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 list element [[s]]$adata[[i]]. The list element has reference-list with list-element 's' having a loci-list adata with list-element 'i storing qualitative data.
`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. condOrder=-1 means the reference is known-non contributor!
`knownRef`	Specify known references from refData (index). For instance knownRef=(1,2) means that reference 1 and 2 is known allele samples in the hypothesis. This is affected by fst-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.

gammadnamix documentation built on May 2, 2019, 4:59 p.m.