generate_sample

Helper function called by both posterior.tidylda and predict.tidylda to
 generate samples from the posterior.

internal

Implements an algorithm for Latent Dirichlet
Allocation (LDA), Blei et at. (2003) <https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf>,
using style conventions from the 'tidyverse',
Wickham et al. (2019)<doi:10.21105/joss.01686>,
and 'tidymodels', Kuhn et al.<https://tidymodels.github.io/model-implementation-principles/>.
Fitting is done via collapsed Gibbs sampling.
Also implements several novel features for LDA such as guided models and
transfer learning.

Thomas W Jones

tidylda

Latent Dirichlet Allocation Using 'tidyverse' Conventions

Tommy Jones

Brendan Knapp

Barum Park

generate_sample function

<dl><dt>dir_par</dt>
<dd>matrix of Dirichlet hyperparameters, one column per</dd>
<dt>matrix</dt>
<dd>character of "theta" or "beta", indicating which posterior
matrix <code>dir_par</code>'s columns are from.</dd>
<dt>times</dt>
<dd>Integer, number of samples to draw.</dd></dl>

Arguments

Generate a sample of LDA posteriors — generate_sample

<dl>

<dt>dir_par</dt>
<dd>matrix of Dirichlet hyperparameters, one column per</dd>


<dt>matrix</dt>
<dd>character of "theta" or "beta", indicating which posterior
matrix <code>dir_par</code>'s columns are from.</dd>


<dt>times</dt>
<dd>Integer, number of samples to draw.</dd>

</dl>

generate_sample: Generate a sample of LDA posteriors

Description

Usage

Value

Arguments