IAM_VnkNegBin

The dispersion parameter <code>r</code> of Negative Binomial

The probability of failure parameter <code>p</code> of Negative Binomial

The <code>gamma</code> parameter of the Dirichlet

internal

Fits finite Bayesian mixture models with a random number of components. The MCMC algorithm implemented is based on point processes as proposed by Argiento and De Iorio (2019) <arXiv:1904.09733> and offers a more computationally efficient alternative to reversible jump. Different mixture kernels can be specified: univariate Gaussian, multivariate Gaussian, univariate Poisson, and multivariate Bernoulli (latent class analysis). For the parameters characterising the mixture kernel, we specify conjugate priors, with possibly user specified hyper-parameters. We allow for different choices for the prior on the number of components: shifted Poisson, negative binomial, and point masses (i.e. mixtures with fixed number of components).

Bruno Bodin

AntMAN

Anthology of Mixture Analysis Tools

Priscilla Ong

Raffaele Argiento

Maria De Iorio

IAM_VnkNegBin function

Compute the value V(n,k), needed to caclulate the eppf of a Finite Dirichlet process when the prior on the component-weigts of the mixture is a Dirichlet with parameter <code>gamma</code> (i.e. when unnormailized weights are distributed as Gamma(\(\gamma\),1) ) when the prior on the number of componet is Negative Binomial with parameter <code>r</code> and <code>p</code>with mean is mu =1+ r*p/(1-p) TODO: CHECK THIS FORMULA!!!. See Section 9.1.1 of the Paper Argiento de Iorio 2019 for more details — IAM_VnkNegBin

Compute the value V(n,k), needed to caclulate the eppf of a Finite Dirichlet process when the prior on the component-weigts of the mixture is a Dirichlet with parameter <code>gamma</code> (i.e. when unnormailized weights are distributed as Gamma(\(\gamma\),1) ) when the prior on the number of componet is Negative Binomial with parameter <code>r</code> and <code>p</code>with mean is mu =1+ r*p/(1-p) TODO: CHECK THIS FORMULA!!!. See Section 9.1.1 of the Paper Argiento de Iorio 2019 for more details

Description

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