calc_PGtheta_R

Same as utils::calc_PGtheta, but this is for calling from R

internal

Fits keyword assisted topic models (keyATM) using collapsed Gibbs samplers. The keyATM combines the latent dirichlet allocation (LDA) models with a small number of keywords selected by researchers in order to improve the interpretability and topic classification of the LDA. The keyATM can also incorporate covariates and directly model time trends. The keyATM is proposed in Eshima, Imai, and Sasaki (2024) <doi:10.1111/ajps.12779>.

Shusei Eshima

keyATM

Keyword Assisted Topic Models

Tomoya Sasaki

Kosuke Imai

Chung-hong Chan

Romain François

Martin Feldkircher

William Lowe

Seo-young Silvia Kim

calc_PGtheta_R function

<dl><dt>theta_tilda</dt>
<dd>Parameters</dd>
<dt>theta</dt>
<dd>Parameters</dd>
<dt>num_doc</dt>
<dd>Number of documents</dd>
<dt>num_topics</dt>
<dd>Number of topics</dd></dl>

Arguments

Calculate the probability for Polya-Gamma Covariate Model — calc_PGtheta_R

<dl>

<dt>theta_tilda</dt>
<dd>Parameters</dd>


<dt>theta</dt>
<dd>Parameters</dd>


<dt>num_doc</dt>
<dd>Number of documents</dd>


<dt>num_topics</dt>
<dd>Number of topics</dd>

</dl>

Calculate the probability for Polya-Gamma Covariate Model

calc_PGtheta_R: Calculate the probability for Polya-Gamma Covariate Model

Description

Usage

Arguments