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initialization = "stm" (including
stmSeed): the sentiment-discourse coefficients
kappa_s were always initialized to zero, because the STM
topic coefficients were read where the content-covariate interaction
coefficients were intended. kappa_t and
kappa_s are now initialized from the STM’s
content-covariate effects (intercept and slope of a document-weighted
least-squares fit on the centered levels of
initializationVar), which reproduces the STM topic-word
distributions exactly for a binary initializationVar. On
the Gadarian example this gives a higher final ELBO and faster
convergence; fits with initialization = "stm" will differ
from sts 1.5. An informative error is now given if stmSeed
has no content covariate matching initializationVar.initialization = "anchor" (the default) and the STM fit
used by initialization = "stm" are now implemented
internally (R/stmPort.R, src/stmfuns.cpp),
adapted from stm 1.3.8 (MIT license; the stm authors are credited in
Authors@R and inst/COPYRIGHTS).textProcessor(),
prepDocuments() and make.heldout(), ported
from stm, so that raw text can be prepared for sts() and
held-out data created without stm.gadarian (from stm) used in the
examples.stmSeed.sts() now gives an informative error for an unknown
initialization value.R.rsp::asis
engine.textProcessor())
to Imports and removed stm, knitr and rmarkdown.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.