posterior: Draw from the marginal posteriors of a tidylda topic model

In tidylda: Latent Dirichlet Allocation Using 'tidyverse' Conventions

Draw from the marginal posteriors of a tidylda topic model

Description

Sample from the marginal posteriors of a tidylda topic model. This is useful for quantifying uncertainty around the parameters of beta or theta.

Usage

posterior(x, ...)

## S3 method for class 'tidylda'
posterior(x, matrix, which, times, ...)

Arguments

x	An object of class tidylda.
...	Other arguments, currently not used.
matrix	A character of either 'theta' or 'beta', indicating from which matrix to draw posterior samples.
which	Row index of theta, for document, or beta, for topic, from which to draw samples. which may also be a vector of indices to sample from multiple documents or topics simultaneously.
times	Integer, number of samples to draw.

Value

posterior returns a tibble with one row per parameter per sample.

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 beta).

References

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

Examples

# load some data
data(nih_sample_dtm)

# fit a model
set.seed(12345)

m <- tidylda(
  data = nih_sample_dtm[1:20, ], k = 5,
  iterations = 200, burnin = 175
)

# sample from the marginal posterior corresponding to topic 1
t1 <- posterior(
  x = m,
  matrix = "beta",
  which = 1,
  times = 100  
)

# sample from the marginal posterior corresponding to documents 5 and 6
d5 <- posterior(
  x = m,
  matrix = "theta",
  which = c(5, 6),
  times = 100
)

tidylda documentation built on July 26, 2023, 5:34 p.m.