posterior.lda_topic_model: Draw from the posterior of an LDA topic model

In textmineR: Functions for Text Mining and Topic Modeling

Description

This function takes an object of class lda_topic_model and draws samples from the posterior of either phi or theta. This is useful for quantifying uncertainty around parametersof the final model.

Usage

## S3 method for class 'lda_topic_model'
posterior(object, which = "theta", num_samples = 100, ...)

Arguments

object	An object of class lda_topic_model
which	A character of either 'theta' or 'phi', indicating from which matrix to draw posterior samples
num_samples	Integer number of samples to draw
...	Other arguments to be passed to TmParallelApply.

Value

Returns a data frame where each row is a single sample from the posterior. Each column is the distribution over a single parameter. The variable var is a facet for subsetting by document (for theta) or topic (for phi).

References

Heinrich, G. (2005) Parameter estimation for text analysis. Technical report. http://www.arbylon.net/publications/text-est.pdf

Examples

## Not run: 
a <- posterior(object = nih_sample_topic_model, which = "theta", num_samples = 20)

plot(density(a$t1[a$var == "8693991"]))

b <- posterior(object = nih_sample_topic_model, which = "phi", num_samples = 20)

plot(denisty(b$research[b$var == "t_5"]))

## End(Not run)

textmineR documentation built on June 28, 2021, 9:08 a.m.