# Maximum likelihood estimation per locus of the number of contributors to forensic DNA mixtures.

### Description

The `likestim.loc`

function returns the estimation of the number of contributors,
at each locus, obtained by maximizing the likelihood.

### Usage

1 | ```
likestim.loc(mix, freq, refpop = NULL, theta = NULL, loc = NULL)
``` |

### Arguments

`mix` |
a |

`freq` |
a |

`refpop` |
the reference population from which to extract the allele frequencies used in the likelihood
calculation. Default set to NULL, 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 `loc`

x 2. The first colum, `max`

, gives the maximum likelihood estimation
of the number of contributors for each locus in row. The second column, `maxvalue`

,
gives the corresponding likelihood value.

### Author(s)

Hinda Haned <contact@hindahaned.info>

### 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`

for multiloci estimations

### Examples

1 2 3 4 5 6 |