| maxmult {hyperdirichlet} | R Documentation |
Gives a maximum likelihood estimate for the parameters of a Dirichlet distribution, on the basis of datapoints drawn from a multivariate beta distribution
maxmult(M, start_a = NULL, give = FALSE, method = "nlm", ...)
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() |
Finds the maximum likelihood estimate from the equation 7 of Mosimann 1962.
The nlm() function appears to be better suited to this problem
than optim().
Robin K. S. Hankin
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.
data(pollen) maxmult(pollen, start_a=c(51.81, 0.987, 5.332, 1.961))