# Maximum likelihood estimation of the number of contributors to a forensic DNA mixture for a set of loci

### Description

The `likestim`

function gives multiloci estimation of the number of contributors to a forensic DNA mixture
using likelihood maximization.

### Usage

1 |

### Arguments

`mix` |
a |

`freq` |
a |

`refpop` |
the reference population from which to extract the allele frequencies used in the likelihood
calculation. If |

`theta` |
a float from [0,1[ giving Wright's Fst coefficient. |

`loc` |
loci to be considered in the estimation. Default (set to NULL) corresponds to all loci. |

### Details

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.

### Value

A matrix of dimension 1 x 2, the first column, `max`

, gives the maximum likelihood estimation of the number of contributors,
the second column
gives the corresponding likelihood value `maxvalue`

.

### Author(s)

Hinda Haned <h.haned@nfi.minvenj.nl>

### References

Haned H, Pene L, Lobry JR, Dufour AB, Pontier D.
Estimating the number of contributors to forensic DNA mixtures: Does maximum likelihood
perform better than maximum allele count? * J Forensic Sci*, accepted 2010.

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

### See Also

`likestim.loc`

for maximum of likelihood estimations per locus

### Examples

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