Description Usage Arguments Value Examples
View source: R/AM_mix_weights_prior.R
Generate a configuration object to specify a prior on the hyperparameter γ for the Dirichlet prior on the mixture weights. We assume γ \sim Gamma(a,b). Alternatively, we can fix γ to a specific value. Default is γ=1/N, where N is the number of observations. In AntMAN we assume the following parametrization of the Gamma density:
p(x\mid a,b )= \frac{b^a x^{a-1}}{Γ(a)} \exp\{ -bx \}, \quad x>0.
1 |
a |
The shape parameter a of the Gamma prior. |
b |
The rate parameter b of the Gamma prior. |
gamma |
It allows to fix γ to a specific value. |
init |
The init value for γ, when we assume γ random. |
A AM_mix_weights_prior
object. This is a configuration list to be used as mix_weight_prior
argument for AM_mcmc_fit
.
1 2 3 4 | AM_mix_weights_prior_gamma (a=1, b=1)
AM_mix_weights_prior_gamma (a=1, b=1, init=1)
AM_mix_weights_prior_gamma (gamma = 3)
AM_mix_weights_prior_gamma ()
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