sim_LDA_TS_data | R Documentation |
For a given set of covariates X
; parameters
Beta
, Eta
, rho
, and err
; and
document-specific time stamps tD
and lengths N
),
simulate a document-by-topic matrix.
Additional structuring variables (the numbers of topics (k), terms (V),
documents (M), segments (S), and covariates per segment (C))
are inferred from input objects.
sim_LDA_TS_data(N, Beta, X, Eta, rho, tD, err = 0, 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 |
|
X |
|
Eta |
|
rho |
Vector of integer-conformable time locations of changepoints or
|
tD |
Vector of integer-conformable times of the documents. Must be
of length M (as determined by |
err |
Additive error on the link-scale. Must be a non-negative
|
seed |
Input to |
A document-by-term matrix
of counts (dim: M x V).
N <- c(10, 22, 15, 31)
tD <- c(1, 3, 4, 6)
rho <- 3
X <- cbind(rep(1, 4), 1:4)
Eta <- cbind(c(0.5, 0.3, 0.9, 0.5), c(1.2, 1.1, 0.1, 0.5))
Beta <- matrix(c(0.1, 0.1, 0.8, 0.2, 0.6, 0.2), 2, 3, byrow = TRUE)
err <- 1
sim_LDA_TS_data(N, Beta, X, Eta, rho, tD, err)
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