| as_arules_sequences | Convert sequence data to cSPADE transaction input |
| as_grpstring_data | Create GrpString-compatible event and string inputs |
| as_igraph_transition_network | Convert a transition network to an igraph object |
| as_seqhmm_sequences | Convert sequence data to seqHMM observations |
| as_traminer_sequences | Convert sequence data to a TraMineR state-sequence object |
| audit_sequence_analysis | Audit a gp3sequences analysis object |
| audit_sequence_data | Audit Long-Format Sequence Data |
| bootstrap_sequence_clusters | Bootstrap sequence-cluster stability |
| bootstrap_sequence_group_difference | Bootstrap a sequence group difference |
| bootstrap_transition_network | Bootstrap transition-network edge weights |
| cluster_sequences | Cluster sequences from a distance object |
| compare_sequence_analysis_results | Compare two gp3sequences analysis results |
| compare_sequence_groups | Compare sequence groups descriptively |
| compare_sequence_hmms | Compare fitted sequence HMMs descriptively |
| compare_sequence_panel_changes | Compare within-panel sequence changes |
| compare_sequence_subsequences | Compare subsequence prevalence between groups |
| compute_sequence_distance | Compute pairwise sequence distances |
| create_consensus_sequence | Create an aligned-position consensus sequence |
| create_sequence_cluster_ensemble | Create a sequence-cluster ensemble |
| create_transition_network | Create a transition network from ordered sequences |
| declare_sequence_comparison_design | Declare a sequence group-comparison design |
| decode_covariate_sequence_states | Decode states from a covariate-dependent HMM |
| decode_multichannel_sequence_states | Decode latent states from a multichannel HMM |
| decode_sequence_states | Decode hidden states from a fitted HMM |
| detect_transition_communities | Detect descriptive transition communities |
| encode_sequence_data | Encode Ordered Sequence States |
| extract_representative_sequences | Extract representative sequences from clusters |
| extract_sequence_ngrams | Extract Contiguous Sequence N-Grams |
| extract_sequence_subsequences | Extract bounded non-contiguous sequence subsequences |
| filter_sequence_motifs | Filter Sequence Motif Summaries |
| filter_sequence_subsequences | Filter non-contiguous subsequence summaries |
| fit_covariate_sequence_hmm | Fit a covariate-dependent categorical hidden Markov model |
| fit_higher_order_transition_model | Fit a higher-order transition model |
| fit_multichannel_sequence_hmm | Fit a multichannel categorical hidden Markov model |
| fit_sequence_hmm | Fit a categorical hidden Markov model |
| fit_sequence_hmm_mixture | Fit a mixture of categorical hidden Markov models |
| fit_time_varying_sequence_model | Fit a time-varying sequence condition model |
| format_consensus_sequence | Format consensus sequences as paths |
| format_sequence_motif_positions | Format Sequence Motif Position Summaries |
| format_sequence_motifs | Format Sequence Motif Summaries |
| format_sequence_paths | Format Ordered Sequence Paths |
| gp3sequences-package | gp3sequences: Transparent Analysis of Ordered Categorical... |
| plot_consensus_sequence | Plot a consensus sequence |
| plot_multichannel_sequence_hmm | Plot multichannel HMM emission profiles |
| plot_sequence_cluster_silhouette | Plot sequence-cluster silhouette values |
| plot_sequence_distance_heatmap | Plot a sequence-distance heatmap |
| plot_sequence_entropy | Plot position-wise state entropy |
| plot_sequence_group_comparison | Plot a descriptive sequence-group comparison |
| plot_sequence_group_inference | Plot sequence group inference |
| plot_sequence_index | Plot a sequence index heatmap |
| plot_sequence_motif_positions | Plot Sequence Motif Positions |
| plot_sequence_motifs | Plot Sequence Motif Summaries |
| plot_sequence_panel_changes | Plot longitudinal sequence changes |
| plot_sequence_state_distribution | Plot state distributions over aligned positions |
| plot_sequence_subsequences | Plot non-contiguous subsequence summaries |
| plot_time_varying_sequence_model | Plot predicted time-varying sequence probabilities |
| plot_transition_network | Plot a first-order transition network |
| predict_covariate_transition_probabilities | Predict covariate-dependent transition probabilities |
| predict_next_state | Predict the next state from a transition model |
| predict_time_varying_sequence_model | Predict a time-varying sequence model |
| prepare_gp3tools_sequences | Prepare common gp3tools-style sequence outputs |
| prepare_sequence_data | Prepare Long-Format Sequence Data |
| prepare_sequence_panel | Prepare longitudinal or panel sequence data |
| sequence_capabilities | Report gp3sequences capabilities and optional integrations |
| summarise_consensus_agreement | Summarise consensus agreement |
| summarise_covariate_sequence_hmm | Summarise a covariate-dependent HMM |
| summarise_multichannel_sequence_hmm | Summarise a multichannel sequence HMM |
| summarise_sequence_cluster_stability | Summarise sequence-cluster stability |
| summarise_sequence_distance | Summarise a sequence-distance object |
| summarise_sequence_group_inference | Summarise sequence group inference |
| summarise_sequence_hmm | Summarise a fitted sequence HMM |
| summarise_sequence_motif_positions | Summarise Sequence Motif Positions |
| summarise_sequence_motifs | Summarise Contiguous Sequence Motifs |
| summarise_sequence_panel | Summarise a sequence panel |
| summarise_sequence_states | Summarise Sequence States |
| summarise_sequence_subsequences | Summarise non-contiguous subsequences |
| summarise_sequence_transitions | Summarise Adjacent Sequence Transitions |
| summarise_time_varying_sequence_model | Summarise a time-varying sequence model |
| summarise_transition_centrality | Summarise transition-network centrality |
| test_sequence_group_difference | Test a sequence group difference |
| validate_sequence_clusters | Validate sequence clusters descriptively |
| validate_sequence_data | Validate Long-Format Sequence Data |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.