Description Usage Arguments Value Examples
For a given set of parameters alpha
and Beta
and
document-specific total word counts, simulate a document-by-term matrix.
Additional structuring variables (the numbers of topics (k),
documents (M), terms (V)) are inferred from input objects.
1 | sim_LDA_data(N, Beta, alpha = NULL, Theta = NULL, seed = NULL)
|
N |
A vector of document sizes (total word counts). Must be integer conformable. Is used to infer the total number of documents. |
Beta |
|
alpha |
Single positive numeric value for the Dirichlet distribution
parameter defining topics within documents. To specifically define
document topic probabilities, use |
Theta |
|
seed |
Input to |
A document-by-term matrix
of counts (dim: M x V).
1 2 3 4 5 6 7 |
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