# MultLogLik: Evaluates the Multinomial likelihood under the single f model In HWEBayes: Bayesian investigation of Hardy-Weinberg Equilibrium via estimation and testing.

## Description

Evaluates the Multinomial likelihood under the single f model. The normalizing constant is not included. This function is called by a number of other functions, and should not be needed.

## Usage

 `1` ```MultLogLik(x, nvec, paramch = 1) ```

## Arguments

 `x` a set of k-1 baseline logits, where k is the number of alleles), and a transformed version of f. Hence a vector of length k. The transformation adopted depends on the value of `paramch`. `nvec` vector of genotype frequencies in the order n_{11}, n_{21}, ..., n_{k1}, n_{22}, ..., n_{k2}, ..., n_{kk}. `paramch` a variable that if =1 assumes f is on the range (-1,+1) before transformation, and if =2 assumes on the range (f_{\min},+1).

## Value

 `MultLoglik` The value of the (unnormalized) multinomial log-likelihood.

## Note

`MultLogLikP` also calculates the mulinimial likelihood using a different parameterization.

## Author(s)

Jon Wakefield ([email protected])

## References

Wakefield, J. (2010). Bayesian methods for examining Hardy-Weinberg equilibrium. Biometrics; Vol 66:257-65

Weir, B.S. (1996). Genetic Data Analysis II. Sunderland MA: Sinauer.

`SinglefReject`, `MultLogLikP`