bivarhr 0.1.6
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.