Fit a custom tgmrf latent block

One front door for inference over a user-defined tgmrf() latent block's hyperparameter vector theta. mode selects the inference engine, all of which share the same Laplace body for (beta, z) | theta:

• "imh" (default) – Tier-1 exact MCMC: the Laplace body plus an independence-Metropolis bias correction over theta (the "Laplace + MH debias" composition).

• "nuts" – Tier-1 exact MCMC: NUTS over the marginal theta posterior.

• "vi" – Tier-2 structured: a single-path Pathfinder Gaussian fit of the theta posterior (no bias correction).

• "nuts_joint" – Tier-1 exact MCMC sampling the FULL joint (beta, z, theta) rather than the Laplace-marginalized theta (requires a C++-backend block, see tgmrf_cpp()).

The inference method is an argument, not a parallel verb.

Usage

tulpa_tgmrf(
  y,
  n_trials,
  X,
  block,
  family = "binomial",
  phi = 1,
  re_idx = NULL,
  n_re_groups = 0L,
  sigma_re = 1,
  mode = c("imh", "nuts", "vi", "nuts_joint"),
  control = list(),
  ...
)

Arguments

y, n_trials, X

Response, binomial trial counts (or NULL), and the fixed-effect design matrix.

block

A tgmrf() latent block.

family, phi

Observation family and its dispersion.

re_idx, n_re_groups, sigma_re

Optional scalar random-intercept structure.

mode

Inference engine: "imh", "nuts", "vi", or "nuts_joint".

control

A list of numerical / tuning knobs for the chosen mode (e.g. n_iter, warmup, thin, scale for "imh"; epsilon, max_depth, target_accept for the NUTS modes; n_draws, max_lbfgs, lbfgs_tol for "vi"; plus the shared pilot_axis_points, max_iter, tol, n_threads, verbose). An unknown knob for the chosen mode errors rather than being silently ignored.

...

Individual control knobs may also be passed directly by name; they are merged into control (a named argument here wins over the same name inside control).

Value

A tulpa_tgmrf / tulpa_fit object; $backend and $mode record the engine used.

See also

tgmrf() for the block, tgmrf_cpp() for the compiled-block form.

Examples

if (FALSE) { # \dontrun{
# `block` is a tgmrf latent block (from tgmrf() / tgmrf_cpp()); the inference
# method is an argument, not a parallel verb. See vignette("tgmrf").
fit <- tulpa_tgmrf(y, rep(1L, length(y)), X, block = blk, mode = "imh")
} # }