# Likelihood of DNA evidence conditioned on a given hypothesis

### Description

likEvid allows the calculation of likelihood for a piece of DNA evidence, for any number of replicates, any number of contributors, and when drop-in and drop-out are possible.

### Usage

1 | ```
likEvid(Repliste, T, V, x, theta, prDHet, prDHom, prC, freq)
``` |

### Arguments

`Repliste` |
vector of alleles present at a given locus for any number of replicates. If there are two replicates, showing alleles 12,13, and 14 respectively, then |

`T` |
vector of genotypes for the known contributors under Hp. Genotype 12/17 should be given as a vector c(12,17) and genotypes 12/17,14/16, should be given as a unique vector: c(12,17,14,16). If T is empty, set to 0. |

`V` |
vector of genotypes for the known non-contributors (see References section) under Hp. See |

`x` |
Number of unknown individuals under H. Set to 0 if there are no unknown contributors. |

`theta` |
thete correction, value must be taken in [0,1) |

`prDHet` |
probability of dropout for heterozygotes. It is possible to assign different values per contributor. In this case, |

`prDHom` |
probability of dropout for homozygotes. See description ofr argument |

`prC` |
probability of drop-in applied per locus |

`freq` |
vector of the corresponding allele frequencies of the analysed locus in the target population |

### Author(s)

Hinda Haned contact@hindahaned.info

### References

Gill, P.; Kirkham, A. & Curran, J. LoComatioN: A software tool for the analysis of low copy number DNA profiles *Forensic Science International*, 2007, 166(2-3), 128-138

Curran, J. M.; Gill, P. & Bill, M. R. Interpretation of repeat measurement DNA evidence allowing for multiple contributors and population substructure *Forensic Science International*, 2005, 148, 47-53

### See Also

`LRmixTK`

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
#load allele frequencies
library(forensim)
data(ngm)
#create vector of allele frequencies
d10<-ngm$tab$D10
# evaluate the evidence under Hp; contributors are the suspect and one unknown,
# dropout probabilities for the suspect and the unknown are the same: 0.2 for heterozygotes,
# and 0.1 for homozygotes.
likEvid(Repliste=c(12,13,14),T=c(12,13),V=0,x=1,theta=0,prDHet=c(0.2,0.2),
prDHom=c(0.04,0.04),prC=0,
freq=d10)
# evaluate the evidence under Hd; contributors are two unknown people, the dropout
# probabilities for the unknowns is kept the same under Hd
likEvid(Repliste=c(12,13,14),T=0,V=0,x=2,theta=0,prDHet=c(0.2,0.2),
prDHom=c(0.04,0.04),prC=0,freq=d10)
``` |

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