R: Topic Models

# Topic Models

## Documentation for package ‘topicmodels’ version 0.2-9

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

AssociatedPress | Associated Press data
build_graph | Construct the adjacency matrix for a topic graph
coerce-method | Different classes for controlling the estimation of topic models
CTM | Correlated Topic Model
CTM-class | Virtual class "TopicModel"
CTM_VEMcontrol-class | Different classes for controlling the estimation of topic models
distHellinger | Compute Hellinger distance
distHellinger.default | Compute Hellinger distance
distHellinger.simple_triplet_matrix | Compute Hellinger distance
dtm2ldaformat | Transform data from and for use with the 'lda' package
get_terms | Extract most likely terms or topics.
get_topics | Extract most likely terms or topics.
LDA | Latent Dirichlet Allocation
LDA-class | Virtual class "TopicModel"
LDAcontrol-class | Different classes for controlling the estimation of topic models
ldaformat2dtm | Transform data from and for use with the 'lda' package
LDA_Gibbscontrol-class | Different classes for controlling the estimation of topic models
LDA_VEMcontrol-class | Different classes for controlling the estimation of topic models
logLik-method | Methods for Function logLik
OPTcontrol-class | Different classes for controlling the estimation of topic models
perplexity | Methods for Function perplexity
perplexity-method | Methods for Function perplexity
posterior-method | Determine posterior probabilities
show-method | Virtual class "TopicModel"
terms-method | Extract most likely terms or topics.
TopicModel-class | Virtual class "TopicModel"
TopicModelcontrol-class | Different classes for controlling the estimation of topic models
topics | Extract most likely terms or topics.
topics-method | Extract most likely terms or topics.