bayessource-package: Package bayessource

In lgaborini/bayessource: Bayesian approach to evaluate whether two datasets come from the same population

Description

Bayesian approach to evaluate whether two sets of multivariate observations come from the same source.

Details

The observations are assumed to be generated by a hierarchical Normal-Inverted Wishart distribution. The hyperparameters can be fitted using additional background data, covering samples from multiple sources.

The package implements a Gibbs sampler to sample from the posteriors, and the computation of the marginal likelihood follows Chib (1995). The Bayes factor can also be computed as a ratio of two marginal likelihoods.

Normal-Inverse-Wishart model

Described in \insertCiteBozza2008Probabilisticbayessource.

Observation level:

• X_{ij} ~ N_p(theta_i, W_i)

  (i = source, j = items from source)

Group level:

• theta_i ~ N_p(μ, B)

• W_i ~ IW_p(n_w, U)

Hyperparameters:

• B, U, n_w, μ

Posterior samples of theta, W^{(-1)} can be generated with a Gibbs sampler.

References

\insertAllCited

See Also

Other core functions: get_minimum_nw_IW(), make_priors_and_init(), marginalLikelihood_internal(), marginalLikelihood(), mcmc_postproc(), samesource_C(), two.level.multivariate.calculate.UC()

lgaborini/bayessource documentation built on Nov. 9, 2021, 2:10 p.m.