# heterozygosity: Heterozygosity at a Locus Using Gene Frequencies In pegas: Population and Evolutionary Genetics Analysis System

## Description

Thes functions compute the mean heterozygosity(ies) from gene frequencies, and return optionally the associated variance(s).

## Usage

 ```1 2 3 4 5 6 7``` ```H(x, ...) ## S3 method for class 'loci' H(x, variance = FALSE, observed = FALSE, ...) ## Default S3 method: H(x, variance = FALSE, ...) heterozygosity(x, variance = FALSE) ```

## Arguments

 `x` an object of class `"loci"`, or vector or a factor. `variance` a logical indicating whether the variance of the estimated heterozygosity should be returned (`TRUE`), the default being `FALSE`. `observed` a logical specifying whether to calculate the observed heterozygosity. `...` unused.

## Details

The argument `x` can be either a factor or a vector. If it is a factor, then it is taken to give the individual alleles in the population. If it is a numeric vector, then its values are taken to be the numbers of each allele in the population. If it is a non-numeric vector, it is a coerced as a factor.

The mean heterozygosity is estimated with:

H = n(1 - SUM (FROM i=1 TO k) p_i^2)/(n - 1)

where n is the number of genes in the sample, k is the number of alleles, and p_i is the observed (relative) frequency of the ith allele.

## Value

For the default method: a numeric vector of length one with the estimated mean heterozygosity (the default), or of length two if the variance is returned.

For the `"loci"` method: a numeric matrix with one, two, or three columns with a row for each locus and the values of heterozygosity as columns.

## References

Nei, M. (1987) Molecular evolutionary genetics. New York: Columbia University Press.

`theta.s`
 ```1 2 3 4 5 6 7 8 9``` ```data(jaguar) H(jaguar, TRUE, TRUE) ## use the (old) default method: ## convert the data and compute frequencies: S <- summary(jaguar) ## compute H for all loci: sapply(S, function(x) H(x\$allele)) ## ... and its variance sapply(S, function(x) H(x\$allele, variance = TRUE)) ```