compute_ngme_sgld_samples: Refit an Existing ngme Object with SGLD and Extract Samples
In ngme2: Linear Latent Non-Gaussian Models with Flexible Distributions

compute_ngme_sgld_samples

R Documentation

Refit an Existing ngme Object with SGLD and Extract Samples

Description

Run one additional SGLD stage (warm-started from an existing 'ngme' fit), then extract posterior-like samples from stored trajectories.

Usage

compute_ngme_sgld_samples(
  fit,
  iterations = 4000,
  optimizer = sgld(stepsize = 0.01, temperature = 1),
  burnin = 100,
  n_batch = 20,
  n_parallel_chain = 4,
  alpha = 0.6,
  t0 = 10,
  start_sd = 0.2,
  seed = Sys.time(),
  verbose = FALSE,
  name = "all",
  burnin_iter = 0,
  thinning = 1,
  n_gibbs_samples = NULL,
  apply_transform = TRUE,
  combine_chains = TRUE,
  control_opt = NULL,
  ...
)

Arguments

`fit`	existing fitted 'ngme' object (can be obtained with any optimizer).
`iterations`	optimization iterations for the SGLD stage.
`optimizer`	optimizer for the sampling stage; must be 'sgld(...)'.
`burnin`	burn-in iterations before optimization.
`n_batch`	number of optimization checkpoints.
`n_parallel_chain`	number of parallel chains.
`alpha`	polynomial schedule exponent used by 'poly_decay(alpha, t0)'.
`t0`	non-negative schedule offset.
`start_sd`	standard deviation for randomized chain initialization.
`seed`	random seed for SGLD stage.
`verbose`	logical; print optimization progress.
`name`	parameter block to extract: '"all"' (default), latent model name, or '"general"'.
`burnin_iter`	non-negative integer used both as optimizer schedule warmup ('stepsize_schedule_burnin_iter') and as explicit trajectory trimming before sampling.
`thinning`	positive integer thinning interval.
`n_gibbs_samples`	optional positive integer. If supplied, override 'control_ngme$n_gibbs_samples' for the SGLD refit stage only; otherwise inherit the value from 'fit'.
`apply_transform`	logical; apply parameter transforms to user scale.
`combine_chains`	logical; if 'TRUE', return one combined data.frame, otherwise return one data.frame per chain.
`control_opt`	optional pre-built 'control_opt' object for the SGLD stage. If supplied, it is used directly (with 'store_traj' forced to 'TRUE').
`...`	additional arguments forwarded to [control_opt()] when 'control_opt' is 'NULL'.