Draw from the per-document topic-proportion posterior — posterior_theta

The variational (Laplace) posterior of each document's logit-topic vector is eta_d ~ N(lambda_d, nu_d), both stored on a faSTM fit. This draws nsims samples of theta per document by sampling eta and applying the softmax (with the reference topic appended as 0). This is the pure-R equivalent of topica's posterior_theta_samples; no Rust call is needed because eta + nu fully describe the posterior. Feeds estimateEffect()'s method of composition.

Usage

posterior_theta_samples(model, nsims = 100L, seed = NULL)

Arguments

model: A faSTM fit (from stm()).
nsims: Number of posterior draws.
seed: Optional integer seed for reproducible draws.

Value

A nsims-length list of D x K theta matrices.