NEWS
bivarhr 0.1.6 (2026-07-06)
CRAN compliance
- All packages listed under
Suggests are now used conditionally, as
required by "Writing R Extensions". Every function that relies on a
suggested package (bnlearn, sensemakr, CausalImpact, vars,
RTransferEntropy, MASS, openxlsx) now checks for it with
requireNamespace() and raises an informative error if it is missing.
- All
\donttest examples that exercise a suggested package are now
wrapped in if (requireNamespace(<pkg>, quietly = TRUE)) (or, for the
Stan-based functions, if (interactive() && requireNamespace("cmdstanr"))),
so they are skipped under _R_CHECK_DEPENDS_ONLY_=true instead of
failing. This resolves the CRAN check failure in the run_hmm example.
run_hmm() no longer depends on depmixS4 (which was archived from
CRAN on 2026-07-04). The bivariate Poisson HMM is now fitted by a
self-contained base-R implementation of the Baum-Welch (EM) algorithm
with a numerically stable log-space forward-backward pass, multi-start
restarts, and Viterbi decoding. depmixS4 has been dropped from
Suggests.
Robustness improvements
- Output directories are now explicit function arguments
(
dir_csv, dir_out, dir_figs) instead of global variables read
from the caller's environment. They default to NULL, in which case
the functions no longer write to disk. Affected functions: run_hmm(),
run_dbn(), run_varx(), run_sensemakr(), run_synth_bsts(),
run_transfer_entropy(), run_eba(), rolling_oos().
run_eba() now takes control_combos as an explicit argument instead
of reading it from the global environment.
run_hmm() now calls depmixS4::fit() explicitly, so it works without
attaching depmixS4 to the search path.
run_varx() now coerces its input to a data.table internally, so it
accepts a plain data.frame.
- Fixed a latent bug in
smoketest_floor_elpd_invariance() that called a
non-existent fit_one_internal(); it now calls fit_one().
- Removed a duplicate definition of
export_results_xlsx() that shadowed
the fully featured implementation.
- Dropped unused
ggplot2 and bayesplot entries from Suggests.
bivarhr 0.1.0
- Initial package release.
- Bivariate hurdle model implementation.
- Time-series analysis functions.