dirichlet.mle.Rd
Maximum likelihood estimation of the parameters of the Dirichlet distribution
dirichlet.mle(x, weights=NULL, eps=10^(-5), convcrit=1e-05, maxit=1000, oldfac=.3, progress=FALSE)
x | Data frame with \(N\) observations and \(K\) variables of a Dirichlet distribution |
---|---|
weights | Optional vector of frequency weights |
eps | Tolerance number which is added to prevent from logarithms of zero |
convcrit | Convergence criterion |
maxit | Maximum number of iterations |
oldfac | Convergence acceleration factor. It must be a parameter between 0 and 1. |
progress | Display iteration progress? |
A list with following entries
Vector of \(\alpha\) parameters
The concentration parameter \(\alpha_0=\sum_k \alpha_k\)
Vector of proportions \(\xi_k=\alpha_k / \alpha_0\)
Minka, T. P. (2012). Estimating a Dirichlet distribution. Technical Report.
For simulating Dirichlet vectors with matrix-wise
\(\bold{\alpha}\) parameters see dirichlet.simul
.
For a variety of functions concerning the Dirichlet distribution see the DirichletReg package.