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Event Sequences: Sequenzo and TraMineR Mapping

This page maps Sequenzo event-sequence functions to their closest TraMineR counterparts.

What This Section Covers

This section focuses on event-sequence workflows: creating event-sequence objects, mining subsequences, comparing groups, and plotting event-pattern results.

For TraMineR users, this is the event-sequence analysis layer (seqe* family and related plot methods).

Mapping Table

Sequenzo functionTraMineR counterpartNotes
EventSequenceData.from_tse()/from_state_sequences()seqecreateBuild event-sequence objects from TSE input or from state sequences.
find_frequent_subsequencesseqefsubDirect conceptual match for frequent subsequence mining.
count_subsequence_occurrencesseqeapplysubCount subsequence matches per sequence; counting rules align with countMethod in seqeconstraint().
compare_groupsseqecmpgroupDirect conceptual match for discriminant subsequences across groups.
check_event_subsequence_containmentseqecontainCheck whether a target subsequence appears in each sequence.
plot_subsequence_frequenciesplot.subseqelistPlot support/frequency for mined subsequences.
plot_event_parallel_coordinatesseqpcplot / plot.seqelist(type="pc")Parallel-coordinate view of event sequencing.
plot_subsequence_group_contrastsplot.subseqelistchisqPlot group contrasts using frequency or residual views.
plot_event_dynamicsTraMineRextras seqedplotSurvival-style or binned event-rate views of event timing.
compute_event_transition_matrixseqetmPractical helper for adjacent event-order summaries; not the same as a simultaneous-event transition in TraMineR.
convert_event_sequences_to_tseseqe2tseConvert event-sequence objects to TSE-style table format.
event_sequence_helpers (is_event_sequence, is_event_sequence_collection, get_event_sequence_lengths, get_event_sequence_weights)is.eseq, is.seqelist, seqelength, seqeweightHelper functions for object checks and metadata access.

Author

Code and documentation: Yuqi Liang

Reference

Ritschard, G., Bürgin, R., & Studer, M. (2013). Exploratory Mining of Life Event Histories. In J. J. McArdle & G. Ritschard (Eds.), Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences (pp. 221–253). Routledge.