Description Usage Arguments Details Value Examples
This function computes the prior on the number of clusters, i.e. occupied component of the mixture for a Finite Dirichlet process when the
prior on the component-weights of the mixture is a Dirichlet with parameter gamma
(i.e. when unnormalized weights are distributed as
Gamma(γ,1)). This function can be used when the prior on the number of components is Negative Binomial with parameter r>0 and
0<p<1, with mean mu =1+ r*p/(1-p). See \insertCiteargiento2019infinityAntMAN for more details.
1 | AM_prior_K_NegBin(n, gamma, r, p)
|
n |
The sample size. |
gamma |
The |
r |
The dispersion parameter |
p |
The probability of failure parameter |
There are no default values.
an AM_prior
object, that is a vector of length n, reporting the values V(n,k)
for k=1,...,n
.
1 2 3 4 5 6 7 | n <- 50
gamma <- 1
r <- 0.1
p <- 0.91
gam_nb <- 0.2381641
prior_K_nb <- AM_prior_K_NegBin(n,gam_nb,r,p)
plot(prior_K_nb)
|
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