Changelog
Source:NEWS.md
lagdynamics 0.32
CRAN release: 2026-07-21
New features
-
transitions()now reads inference results, not only fitted models. It accepts the output ofbootstrap_lsa(),certainty_lsa(),stability_lsa(),permute_lsa(),compare_lsa(),bayes_compare_lsa()andlsa_lags(), and returns the same tidy one-row-per-transition data frame.significant = TRUEkeeps the transitions the method itself flags, andsort = "strength"orders them by that method’s signed effect. Previously the per-transition table of an inference result was reachable only throughas.data.frame(), because the print methods show a header summary alone. - The
transitions()generic is nowtransitions(fit, ...), so each class declares only the arguments backed by columns it actually has. Existing calls on a fit are unaffected.
Documentation
- Vignettes restore the user’s
options()after changingdigits, as CRAN requires. - Vignettes read every result with
transitions()rather than coercing it withas.data.frame(), and select rows with thesignificantargument rather than subsetting. - Removed the citations, reference lists, DOIs, documentation URLs and linked author metadata that 0.31 added to the shipped vignettes.
lagdynamics 0.31
CRAN candidate
- Prepared the package for first CRAN submission.
- Moved
ggplot2andcographfrom Suggests to Imports so the plotting surface works out of the box; plotting examples now run during checks. The analytical core still depends only on base R. - Added a dedicated interoperability vignette covering wide data, long event logs,
tna,Nestimate,cograph, andlsa_to_tna(). - Added linked author metadata and Dynalytics framework links to all shipped vignettes.
- Restored
lsa_to_tna()for handing anlsafit totnatooling. - Added ingestion of
Nestimate::build_network()netobjects through their prepared sequence data. - Stored the bundled
engagementdata as a data frame sotna::tna(engagement)works directly. - Removed dead package-site URLs from CRAN-visible metadata.
- Added future CRAN installation instructions to the README.
- Included
NEWS.mdin the source package.
lagdynamics 0.3.0
Interoperability and documentation
- Added integration tests for
cograph,Nestimate, and the Dynalytics evidence surface. - Added native TNA-style aliases:
weights = "tna"andweights = "relative"now map to transition probabilities. - Updated plotting documentation and vignettes to use
weights = "tna"for probability-weighted transition networks. - Added and reorganised vignettes:
-
intro: conceptual overview and package map. -
lagdynamics: concise quick start. -
workflow: complete applied workflow. -
interop: interoperability with sibling packages. -
lag-transition-networks: transition-network interpretation. -
confirmatory: evidence and uncertainty workflow. -
plotting: plot gallery.
-
- Removed public documentation references to unexported internals.
- Made long-format input more flexible:
actionis the only mandatory long-format column, with optionalactor,session,time, andorder. - Added warnings for single-sequence bootstrap and permutation cases where the requested procedure has limited inferential meaning.
lagdynamics 0.2.0
Confirmatory workflow and group comparison
- Added the Dynalytics-style confirmatory evidence battery:
certainty_lsa(),bootstrap_lsa(),reliability_lsa(),stability_lsa(), andpermute_lsa(). - Added group comparison with
compare_lsa()and Bayesian group comparison withbayes_compare_lsa(). - Added grouped
lsa()fits throughgroup = ..., with grouped methods fortransitions(),nodes(),tests(),initial(), plotting, reliability, and comparison workflows. - Added tidy
as.data.frame()methods for inference and comparison result objects. - Added the unified plotting surface: residual heatmaps, residual networks, TNA probability networks, chord diagrams, sunbursts, uncertainty forests, and group-comparison plots.
- Added native transition and initial probabilities:
transition_probabilities()andinitial(). - Added bundled long-format data for examples and tests.
lagdynamics 0.1.0
Initial implementation
- Created a from-scratch, clean-room implementation of lag sequential analysis for categorical event sequences.
- Added the unified
lsa()constructor and canonical sequence handling throughlsa_data()andlsa_transitions(). - Added five built-in engines:
classical,two_cell,bidirectional,parallel_dominance, andnonparallel_dominance. - Added convenience wrappers:
lsa_classical(),lsa_two_cell(),lsa_bidirectional(),lsa_parallel_dominance(), andlsa_nonparallel_dominance(). - Added the pluggable engine registry:
register_lsa_engine(),get_lsa_engine(),list_lsa_engines(), andunregister_lsa_engine(). - Added tidy reading verbs:
transitions(),nodes(),tests(),initial(), andsummary(). - Added multi-lag helpers with
lsa_lags()andlag_profile(). - Added structural-zero handling through
loops = FALSEand arbitrary structural-zero matrices. - Added experimental
transfer_entropy()for directed categorical information-flow analysis. - Kept runtime dependencies minimal: only base R packages are imported (
grDevices,grid,stats, andutils).