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The DNAmixtures package

The features of the DNAmixtures R-package include parameter-fitting, evaluation of the likelihood, prediction of genotypes, and visual diagnostics.

http://dnamixtures.r-forge.r-project.org/

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The DNAmixtures package | dnamixtures.r-forge.r-project.org Reviews
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The features of the DNAmixtures R-package include parameter-fitting, evaluation of the likelihood, prediction of genotypes, and visual diagnostics.
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1 DNA mixture
2 DNA mixtures
3 R-package
4 statistical inference
5 mixed profile
6 deconvolution
7 likelihood ratio
8 maximum likelihood
9 genotype
10 evidence
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dnamixtures,by therese graversen,nstallation,utorial,eferences,common forensic applications,efficient exact computation,system requirements,statistical software,hugin,bayesian network software,rhugin,library dnamixtures
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The DNAmixtures package | dnamixtures.r-forge.r-project.org Reviews

https://dnamixtures.r-forge.r-project.org

The features of the DNAmixtures R-package include parameter-fitting, evaluation of the likelihood, prediction of genotypes, and visual diagnostics.

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ISFG - Working Groups/DNA Commission/Software

http://www.isfg.org/Software

The ISFG is supporting OPEN SOURCE software projects in forensic statistics, as well as freely accessible software packages offered to our scientific community. The ISFG is not endorsing any specific software. This is not a complete list of forensic software resources, there are others that may have escaped our attention. Furthermore there are numerous commercially available software solutions for the forensic genetics community. Forensic DNA Statistics website. LRmix Studio Community Edition. You will f...

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The DNAmixtures package

Statistical analysis of DNA mixtures with artefacts. Is a statistical framework for analysis of DNA samples from one or multiple donors. DNAmixtures. Implements a statistical model described in a recent paper, Analysis of Forensic DNA mixtures with Artefacts. That is published with discussion in Journal of the Royal Statistical Society, series C. Computation of likelihood ratios. Deconvolution of the DNA mixture. Combined analysis of multiple traces of DNA. Visual assessment of the statistical modelling.

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