Plot the Energy Diagnostic (E-BFMI)

Creates overlaid histograms of marginal energy and energy transition, along with the E-BFMI statistic. Low E-BFMI indicates poor exploration of the posterior.

Usage

plot_energy(fit)

Arguments

fit

A ratiod_fit object (HMC backend).

Value

A ggplot object (if ggplot2 available) or base R plot.

Details

E-BFMI (Energy Bayesian Fraction of Missing Information) compares the distribution of energy levels to energy transitions. Values below 0.3 indicate the sampler may not be exploring the full posterior. The energy is the Hamiltonian after each iteration's momentum draw; it is centred and differenced within each chain, and the subtitle reports the lowest per-chain E-BFMI (tulpa::energy_bfmi()).

See also

diagnostic_summary(), check_diagnostics()

Examples

# \donttest{
sim <- sim_ratiod(n = 100, family = ratiod_poisson_gamma(), seed = 1)
fit <- tratio(y_num | y_denom ~ x1 + (1 | group), data = sim$data,
              family = ratiod_poisson_gamma(),
              control = list(iter = 1000, chains = 2, seed = 1))
plot_energy(fit)

# }