maxmult {hyperdirichlet} | R Documentation

## Estimation of the multivariate beta distribution

### Description

Gives a maximum likelihood estimate for the parameters of a Dirichlet distribution, on the basis of datapoints drawn from a multivariate beta distribution

### Usage

    maxmult(M, start_a = NULL, give = FALSE, method = "nlm", ...)

### Arguments

`M` | Integer matrix whose rows give multinomial observations
`start_a` | Start point for optimization, with default `NULL` being interpreted as Mosimann's formula 29
`give` | Boolean, with default `FALSE` meaning to return just the point estimate and `TRUE` meaning to return all the output from the optimization routine
`method` | Text string specifying the optimization routine to use. Two values coded: default `nlm` means to use `nlm()` and `optim` meaning to use `optim()`; anything else means to return Mosimann's estimate (equation 29)
`...` | Further arguments passed to `nlm()` or `optim()`

### Details

Finds the maximum likelihood estimate from the equation 7 of Mosimann 1962.

### Note

The `nlm()` function appears to be better suited to this problem than `optim()`.

### Author(s)

Robin K. S. Hankin

### References

J. E. Mosimann 1962. “On the compound multinomial distribution, the multivariate beta-distribution, and correlations among proportions”. Biometrika, volume 49, numbers 1 and 2, pp65-82.

### See Also

`pollen`

### Examples

    data(pollen)
    maxmult(pollen, start_a=c(51.81, 0.987, 5.332, 1.961))

[Package hyperdirichlet version 1.3-8 Index]