Package: gp3sequences 0.3.1

gp3sequences: Transparent Analysis of Ordered Categorical Sequences

Provides transparent, reproducible, and auditable tools for validating, preparing, encoding, summarising, comparing, modelling, and diagnosing ordered categorical sequence data. Supports explicit preprocessing policies, contiguous motifs and bounded subsequences, consensus and group comparisons, edit and transition distances, clustering and stability diagnostics, transition networks, higher-order models, categorical, mixture, multichannel, and covariate hidden Markov models, longitudinal panel workflows, time-varying models, design-aware inference, analysis contracts and provenance audits, and guarded adapters to specialist sequence-analysis packages.

Authors:Stefanos Balaskas [aut, cre]

gp3sequences_0.3.1.tar.gz
gp3sequences_0.3.1.zip(r-4.7-any)gp3sequences_0.3.1.zip(r-4.6-any)gp3sequences_0.3.1.zip(r-4.5-any)
gp3sequences_0.3.1.tgz(r-4.6-any)gp3sequences_0.3.1.tgz(r-4.5-any)
gp3sequences_0.3.1.tar.gz(r-4.7-any)gp3sequences_0.3.1.tar.gz(r-4.6-any)
gp3sequences_0.3.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
gp3sequences/json (API)

# Install 'gp3sequences' in R:
install.packages('gp3sequences', repos = c('https://stefanosbalaskas.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/stefanosbalaskas/gp3sequences/issues

Pkgdown/docs site:https://stefanosbalaskas.github.io

On CRAN:

Conda:

behavioral-analysiscategorical-sequenceseye-trackingeyetrackinghidden-markov-modelhmmlevenshtein-distancelongitudinal-datamotifoptimal-matchingr-programmingreproducible-researchresearchresearch-softwarescanpathssequence-analysissequence-modelingstate-segmentationtransition-matrix

6.03 score 18 scripts 297 downloads 81 exports 0 dependencies

Last updated from:a8494f9d09. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK213
source / vignettesOK175
linux-releaseOK138
macos-releaseOK192
macos-oldrelOK188
windows-develOK124
windows-releaseOK123
windows-oldrelOK108
wasm-releaseOK106

Exports:as_arules_sequencesas_grpstring_dataas_igraph_transition_networkas_seqhmm_sequencesas_traminer_sequencesaudit_sequence_analysisaudit_sequence_databootstrap_sequence_clustersbootstrap_sequence_group_differencebootstrap_transition_networkcluster_sequencescompare_sequence_analysis_resultscompare_sequence_groupscompare_sequence_hmmscompare_sequence_panel_changescompare_sequence_subsequencescompute_sequence_distancecreate_consensus_sequencecreate_sequence_cluster_ensemblecreate_transition_networkdeclare_sequence_comparison_designdecode_covariate_sequence_statesdecode_multichannel_sequence_statesdecode_sequence_statesdetect_transition_communitiesencode_sequence_dataextract_representative_sequencesextract_sequence_ngramsextract_sequence_subsequencesfilter_sequence_motifsfilter_sequence_subsequencesfit_covariate_sequence_hmmfit_higher_order_transition_modelfit_multichannel_sequence_hmmfit_sequence_hmmfit_sequence_hmm_mixturefit_time_varying_sequence_modelformat_consensus_sequenceformat_sequence_motif_positionsformat_sequence_motifsformat_sequence_pathsplot_consensus_sequenceplot_multichannel_sequence_hmmplot_sequence_cluster_silhouetteplot_sequence_distance_heatmapplot_sequence_entropyplot_sequence_group_comparisonplot_sequence_group_inferenceplot_sequence_indexplot_sequence_motif_positionsplot_sequence_motifsplot_sequence_panel_changesplot_sequence_state_distributionplot_sequence_subsequencesplot_time_varying_sequence_modelplot_transition_networkpredict_covariate_transition_probabilitiespredict_next_statepredict_time_varying_sequence_modelprepare_gp3tools_sequencesprepare_sequence_dataprepare_sequence_panelsequence_capabilitiessummarise_consensus_agreementsummarise_covariate_sequence_hmmsummarise_multichannel_sequence_hmmsummarise_sequence_cluster_stabilitysummarise_sequence_distancesummarise_sequence_group_inferencesummarise_sequence_hmmsummarise_sequence_motif_positionssummarise_sequence_motifssummarise_sequence_panelsummarise_sequence_statessummarise_sequence_subsequencessummarise_sequence_transitionssummarise_time_varying_sequence_modelsummarise_transition_centralitytest_sequence_group_differencevalidate_sequence_clustersvalidate_sequence_data

Dependencies:

Effect-size visualizations for sequence analysis: design boundaries
Rendered scalar sequence-effect illustration (synthetic)
Rendered fromestimation-visualization-boundaries.Rmdusingknitr::rmarkdown

Last update: 2026-10-09
Started: 2026-10-09

Ecosystem update — September 2026
Related crossed repeated-measures method
Rendered fromecosystem-update-2026-09.Rmdusingknitr::rmarkdown

Last update: 2026-09-14
Started: 2026-09-14

Bounded Non-Contiguous Subsequence Mining
Why bounded subsequences? | Synthetic sequences | Enumerate occurrences | Sequence-level prevalence | Group comparison | Relation to specialist packages
Rendered fromnoncontiguous-subsequence-mining.Rmdusingknitr::rmarkdown

Last update: 2026-07-26
Started: 2026-07-26

Design-Aware Sequence Group Inference
Why declare the design? | Synthetic randomized groups | Declare and test | Bootstrap interval | Causal language
Rendered fromsequence-inference-and-randomization.Rmdusingknitr::rmarkdown

Last update: 2026-07-26
Started: 2026-07-26

Extended Sequence Visualisations
Synthetic data | Sequence index | State distribution and entropy | Distance and clustering diagnostics | Transition network
Rendered fromextended-sequence-visualisations.Rmdusingknitr::rmarkdown

Last update: 2026-07-26
Started: 2026-07-26

Longitudinal and Panel Sequence Workflows
Scope | Synthetic data | Prepare and audit the panel | Summarise occasions and states | Quantify within-panel change | Reporting
Rendered fromlongitudinal-panel-sequences.Rmdusingknitr::rmarkdown

Last update: 2026-07-26
Started: 2026-07-26

Multichannel and Covariate-Dependent HMMs
Scope and guardrails | Synthetic data | Multichannel model | Covariate-dependent model | Reporting
Rendered frommultichannel-and-covariate-hmms.Rmdusingknitr::rmarkdown

Last update: 2026-07-26
Started: 2026-07-26

Time-Varying Condition Comparisons
Model target | Synthetic repeated sequences | Fit and inspect | Predictions | Transition outcomes | Interpretation
Rendered fromtime-varying-condition-models.Rmdusingknitr::rmarkdown

Last update: 2026-07-26
Started: 2026-07-26

Choosing a Sequence-Analysis Method
Start with the research question | Contiguous motifs | Consensus sequences | Descriptive group comparison | Distances | Clustering, representatives, ensembles, and stability | Transition networks | Higher-order transition models | Hidden and mixture sequence models | Optional adapters | Minimum decision checklist | Focused articles
Rendered fromchoosing-a-sequence-analysis-method.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

Getting Started with gp3sequences
Purpose | Synthetic long-format data | Audit, validate, and prepare | Encode states and inspect basic structure | Discover contiguous motifs | Compare sequences through distances and clustering | Consensus and descriptive group comparison | Transition structure | Continue with focused articles
Rendered fromgetting-started-with-gp3sequences.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

Reproducible Sequence Analysis: A Synthetic Case Study
Study objective | Synthetic study data | Prespecified preparation | Structural summaries | Recurring contiguous motifs | Consensus and condition contrasts | Distance, clustering, and representatives | Transition network and recent-context model | Compact categorical HMM sensitivity description | Assemble report-ready evidence | Interpretation boundary
Rendered fromreproducible-sequence-analysis-case-study.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

Sequence Data Validation and Preparation
Why preparation is explicit | A deliberately problematic synthetic input | Audit without modification | Compact validation contract | Apply explicit preparation policies | Revalidate the canonical result | Errors that require source correction | Reporting recommendations
Rendered fromsequence-data-validation-and-preparation.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

Consensus Sequences and Descriptive Group Comparisons
Scope | Synthetic sequences | Aligned-position consensus | Descriptive group comparison
Rendered fromconsensus-and-group-comparisons.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

Latent Sequence Models and Optional Adapters
Interpretation boundary | Synthetic categorical sequences | Categorical HMM | Mixture HMM | Estimation limitations | Optional ecosystem adapters
Rendered fromlatent-models-and-optional-adapters.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

Sequence Distances, Clustering, and Stability
Synthetic paths | Transparent distance families | Clustering and validation | Subsampling stability | Co-association ensemble | Optional PAM and CLARA interfaces
Rendered fromdistances-clustering-and-stability.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

Transition Networks and Higher-Order Models
Synthetic navigation sequences | First-order transition network | Higher-order transition model | Whole-sequence bootstrap
Rendered fromtransition-networks-and-higher-order-models.Rmdusingknitr::rmarkdown

Last update: 2026-07-23
Started: 2026-07-23

Contiguous Motif Workflow
Scope | Synthetic ordered-state data | Extract contiguous motifs | Summarise, filter, and format motifs | Summarise motif positions | Plot motif prevalence | Plot motif locations | Interpretation boundary
Rendered fromcontiguous-motif-workflow.Rmdusingknitr::rmarkdown

Last update: 2026-07-21
Started: 2026-07-21

Readme and manuals

Help Manual

Help pageTopics
Convert sequence data to cSPADE transaction inputas_arules_sequences
Create GrpString-compatible event and string inputsas_grpstring_data
Convert a transition network to an igraph objectas_igraph_transition_network
Convert sequence data to seqHMM observationsas_seqhmm_sequences
Convert sequence data to a TraMineR state-sequence objectas_traminer_sequences
Audit a gp3sequences analysis objectaudit_sequence_analysis
Audit Long-Format Sequence Dataaudit_sequence_data
Bootstrap sequence-cluster stabilitybootstrap_sequence_clusters
Bootstrap a sequence group differencebootstrap_sequence_group_difference
Bootstrap transition-network edge weightsbootstrap_transition_network
Cluster sequences from a distance objectcluster_sequences
Compare two gp3sequences analysis resultscompare_sequence_analysis_results
Compare sequence groups descriptivelycompare_sequence_groups
Compare fitted sequence HMMs descriptivelycompare_sequence_hmms
Compare within-panel sequence changescompare_sequence_panel_changes
Compare subsequence prevalence between groupscompare_sequence_subsequences
Compute pairwise sequence distancescompute_sequence_distance
Create an aligned-position consensus sequencecreate_consensus_sequence
Create a sequence-cluster ensemblecreate_sequence_cluster_ensemble
Create a transition network from ordered sequencescreate_transition_network
Declare a sequence group-comparison designdeclare_sequence_comparison_design
Decode states from a covariate-dependent HMMdecode_covariate_sequence_states
Decode latent states from a multichannel HMMdecode_multichannel_sequence_states
Decode hidden states from a fitted HMMdecode_sequence_states
Detect descriptive transition communitiesdetect_transition_communities
Encode Ordered Sequence Statesencode_sequence_data
Extract representative sequences from clustersextract_representative_sequences
Extract Contiguous Sequence N-Gramsextract_sequence_ngrams
Extract bounded non-contiguous sequence subsequencesextract_sequence_subsequences
Filter Sequence Motif Summariesfilter_sequence_motifs
Filter non-contiguous subsequence summariesfilter_sequence_subsequences
Fit a covariate-dependent categorical hidden Markov modelfit_covariate_sequence_hmm
Fit a higher-order transition modelfit_higher_order_transition_model
Fit a multichannel categorical hidden Markov modelfit_multichannel_sequence_hmm
Fit a categorical hidden Markov modelfit_sequence_hmm
Fit a mixture of categorical hidden Markov modelsfit_sequence_hmm_mixture
Fit a time-varying sequence condition modelfit_time_varying_sequence_model
Format consensus sequences as pathsformat_consensus_sequence
Format Sequence Motif Position Summariesformat_sequence_motif_positions
Format Sequence Motif Summariesformat_sequence_motifs
Format Ordered Sequence Pathsformat_sequence_paths
Plot a consensus sequenceplot_consensus_sequence
Plot multichannel HMM emission profilesplot_multichannel_sequence_hmm
Plot sequence-cluster silhouette valuesplot_sequence_cluster_silhouette
Plot a sequence-distance heatmapplot_sequence_distance_heatmap
Plot position-wise state entropyplot_sequence_entropy
Plot a descriptive sequence-group comparisonplot_sequence_group_comparison
Plot sequence group inferenceplot_sequence_group_inference
Plot a sequence index heatmapplot_sequence_index
Plot Sequence Motif Positionsplot_sequence_motif_positions
Plot Sequence Motif Summariesplot_sequence_motifs
Plot longitudinal sequence changesplot_sequence_panel_changes
Plot state distributions over aligned positionsplot_sequence_state_distribution
Plot non-contiguous subsequence summariesplot_sequence_subsequences
Plot predicted time-varying sequence probabilitiesplot_time_varying_sequence_model
Plot a first-order transition networkplot_transition_network
Predict covariate-dependent transition probabilitiespredict_covariate_transition_probabilities
Predict the next state from a transition modelpredict_next_state
Predict a time-varying sequence modelpredict_time_varying_sequence_model
Prepare common gp3tools-style sequence outputsprepare_gp3tools_sequences
Prepare Long-Format Sequence Dataprepare_sequence_data
Prepare longitudinal or panel sequence dataprepare_sequence_panel
Report gp3sequences capabilities and optional integrationssequence_capabilities
Summarise consensus agreementsummarise_consensus_agreement
Summarise a covariate-dependent HMMsummarise_covariate_sequence_hmm
Summarise a multichannel sequence HMMsummarise_multichannel_sequence_hmm
Summarise sequence-cluster stabilitysummarise_sequence_cluster_stability
Summarise a sequence-distance objectsummarise_sequence_distance
Summarise sequence group inferencesummarise_sequence_group_inference
Summarise a fitted sequence HMMsummarise_sequence_hmm
Summarise Sequence Motif Positionssummarise_sequence_motif_positions
Summarise Contiguous Sequence Motifssummarise_sequence_motifs
Summarise a sequence panelsummarise_sequence_panel
Summarise Sequence Statessummarise_sequence_states
Summarise non-contiguous subsequencessummarise_sequence_subsequences
Summarise Adjacent Sequence Transitionssummarise_sequence_transitions
Summarise a time-varying sequence modelsummarise_time_varying_sequence_model
Summarise transition-network centralitysummarise_transition_centrality
Test a sequence group differencetest_sequence_group_difference
Validate sequence clusters descriptivelyvalidate_sequence_clusters
Validate Long-Format Sequence Datavalidate_sequence_data