R: Multilevel Supervised Topic Models with Multiple Outcomes

# Multilevel Supervised Topic Models with Multiple Outcomes

## Documentation for package ‘mlstm’ version 0.1.7

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

eLDA_pass_b_fast | One Gibbs sampling sweep for LDA (collapsed) using document–term list.
init_mod_from_count | Initialize LDA/STM state from a (d, v, c) sparse count matrix.
run_lda_gibbs | Collapsed LDA Gibbs sampling for sparse (d, v, c) triplet data.
run_mlstm_vi | Multi-level supervised topic model (MLSTM) via variational inference.
run_stm_vi | Supervised topic model (STM) variational inference with ELBO-based convergence.
set_threads | Set threading options for STM/MLSTM computations
stm_multi_hier_vi_parallel | Variational inference for multi-output supervised topic models with hierarchical prior.
stm_vi_parallel | Variational inference for supervised LDA (single continuous response).