bmm.narrowest.mean.interval.about.centers: bmm.narrowest.mean.interval.about.centers: Compute Bayesian...

In genome/bmm: Variational Bayesian approach to fitting mixtures of beta, binomial, or Gaussian distributions

bmm.narrowest.mean.interval.about.centers: Compute Bayesian credible interval on means

Description

bmm.narrowest.mean.interval.about.centers: Return the narrowest (Bayesian credible) interval of the means that include the centers and a fixed proportion of the probability distribution of the means (e.g., .68 or .95).

Usage

  bmm.narrowest.mean.interval.about.centers(mu, alpha, nu, beta, proportion) 

Arguments

mu	a D x N.c matrix holding the shape parameters for the gamma prior distributions over the u parameters. i.e., mu[d,n] is the shape parameter governing u[d,n]. Introduced in eqn (15).
alpha	a D x N.c matrix holding the rate (i.e., inverse scale) parameters for the gamma prior distributions over the u parameters. i.e., mu[d,n] is the rate parameter governing u[d,n]. Introduced in eqn (15).
nu	a D x N.c matrix holding the hyperparameter values of the shape parameters for the gamma prior distributions over the v parameters. i.e., nu[d,n] is the shape parameter governing v[d,n]. Introduced in eqn (16).
beta	a D x N.c matrix holding the hyperparameter values of the rate (i.e., inverse scale) parameters for the gamma prior distributions over the v parameters. i.e., beta[d,n] is the rate parameter governing v[d,n]. Introduced in eqn (16).
proportion	the percentage of the distribution of each mean to include in the interval (e.g., .68 or .95)

Value

a list with values lb and ub, where each are D x N.c matrices holding the respective lower or upper bounds of the intervals, and centers, which is a D x N.c matrix holding the empirical means sampled from the posterior distribution

genome/bmm documentation built on Aug. 4, 2022, 8:01 a.m.