R: Estimate Parameters of Dirichlet Distribution

fit_dirichlet {MCMCprecision} | R Documentation

## Estimate Parameters of Dirichlet Distribution

### Description

C++ implementation of the fixed-point iteration algorithm by Minka (2000).

### Usage

    fit_dirichlet(x, const, maxit = 1e+05, abstol = 0.1)

### Arguments

`x` | a matrix of Dirichlet samples, one row per observation.
`const` | constant that is added to avoid problems with zeros in `log(x)`. The default is `const = min(x[x>0])*.01`.
`maxit` | maximum number of iterations.
`abstol` | The absolute convergence tolerance: maximum of absolute differences of Dirichlet parameters.

### Details

The algorithm is used to estimate the effective sample size based on samples of posterior model probabilities (see `stationary` and `summary.stationary`).

### References

Minka, T. (2000). Estimating a Dirichlet distribution. Technical Report.

### See Also

`rdirichlet`

### Examples

    x <- rdirichlet(100, c(8,1,3,9))
    fit_dirichlet(x)

[Package MCMCprecision version 0.3.9 Index]