Calculates Likelihood Ratio comparing the probability of two profiles if they are indeed parent-child compared to unrelated. This is the paternity index or PI.

1 2 3 4 |

`parent` |
A matrix consisting of 2 columns and nLoci rows. Each entry in the matrix is the (coded) allele held by the individual. This represents the alleged parent. The relationship is reflexive so it does not matter which profile is labelled parent and child. |

`child` |
See |

`Freqs` |
A list containing two lists labelled loci and freqs. The second list is a list of vectors containing the allele frequencies of each allele at each locus in the multiplex. This argument or both f and n must be specified |

`nLoci` |
The number of loci in the profiles |

`f` |
A concatenated vector of allele frequencies. Specifying this speeds up computation enormously |

`n` |
A vector of length |

A value between 0 and infinity representing support (or lack of support if the value is less than 1) for the hypothesis that the two profiles are parent and child. There is no mutation built into this calculation. This means that the LR will be zero if the profiles do not share at least one allele in common at each locus in the multiplex.

James M. Curran

Buckleton, J, Triggs, C.M., and Walsh, S.J. (2005)*Forensic DNA
Evidence Interpretation*, CRC Press., Boca Raton, FL. p.410

lrSib, IBS

1 2 3 4 | ```
data(fbiCaucs)
P1 = randomProfile(fbiCaucs)
C1 = randomChild(P1, fbiCaucs)
lrPC(P1, C1, fbiCaucs)
``` |

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