# pContrib: Compute the posterior probabilities for P(m|n0) for a given... In DNAtools: Tools for Analysing Forensic Genetic DNA Data

 pContrib R Documentation

## Compute the posterior probabilities for P(m|n0) for a given prior P(m) and observed vector n0 of locus counts

### Description

where m ranges from 1 to \code{m.max} and n0 is the observed locus counts.

### Usage

```pContrib(n0, probs = NULL, m.prior = rep(1/m.max, m.max), m.max = 8, theta = 0)
```

### Arguments

 `n0` Vector of observed allele counts - same length as the number of loci. `probs` List of vectors with allele probabilities for each locus `m.prior` A vector with prior probabilities (summing to 1), where the length of `m.prior` determines the plausible range of m `m.max` Derived from the length of `m.prior`, and if `m.prior=NULL` a uniform prior is speficied by `m.max`: `m.prior = rep(1/m.max,m.max)`. `theta` The coancestery coefficient

### Details

Computes a vector P(m|n0) evaluated over the plausible range 1,...,m.max.

### Value

Returns a vector P(m|n0) for m=1,...,m.max

### Author(s)

Torben Tvedebrink, James Curran

### References

T. Tvedebrink (2014). 'On the exact distribution of the number of alleles in DNA mixtures', International Journal of Legal Medicine; 128(3):427–37. <https://doi.org/10.1007/s00414-013-0951-3>

### Examples

```
## Simulate some allele frequencies:
freqs <-  simAlleleFreqs()
m <- 2
n0 <- sapply(freqs, function(px){
peaks = unique(sample(length(px),
size = 2 * m,
replace = TRUE,
prob = px))
return(length(peaks))
})
## Compute P(m|n0) for m=1,...,4 and the sampled n0
pContrib(n0=n0,probs=freqs,m.max=4)

```

DNAtools documentation built on March 18, 2022, 7:01 p.m.