TraMineR Extension
Euclidean Coordinates for Longitudinal Timelines
Converting between graphical formats
Transform time to event data into a discrete data format
BIC and Likelihood ratio test for comparing two groups
Sequence marginality and gain indicators.
Discrepancy by group.
Data conversion from Fixed Column Event format to TSE.
Adds proportion of occurrences to each level names
Data conversion from Horizontal Spell to STS.
PAM from k-solution of hierarchical clustering
Dynamic index plot
Emlt Plots
Plot method for objects produced by the seqsurv function
Modal state of a variable
Auto-association between states
Competing Trajectory Analysis (CTA)
Definition of an events to states matrix.
Distances between event sequences
Graphical representation of a set of events sequences.
Event sequence length and number of events
Extract association rules using discrete time regression models
Generate random missing elements within a state sequence object
Changing sequence time granularity by aggregating positions
Position wise group-typical states
Dynamic index
Relative Frequency Sequence Plots.
Plotting superposed transversal-entropy curves
Measuring the Degree of Within-Polyadic Similarities
Finding representative sets by group and their quality statistics.
Sequence Analysis Multistate Model (SAMM) procedure
Sequence History Analysis (SHA)
Plot survival curves of the states in sequences
Aligning sequence data on a new start time.
Generate a survfit object for state survival times.
Frequencies of state co-occurrence patterns
Sort sequences by states at the successive positions
Converting into person-period format.
TraMineR Extension
Converting TSE data into STS (state sequences) format.
Collection of ancillary functions and utilities to be used in conjunction with the 'TraMineR' package for sequence data exploration. Includes, among others, specific functions such as state survival plots, position-wise group-typical states, dynamic sequence indicators, and dissimilarities between event sequences. Also includes contributions by non-members of the TraMineR team such as methods for polyadic data and for the comparison of groups of sequences.