PST: Probabilistic Suffix Trees

This package provides functions to analyse state sequences with probabilistic suffix trees (PST), the construction that stores variable length Markov chains (VLMC). The PST library allows to learn VLMC models and includes many additional tools and features to analyse sequence data with these models: visualization tools, functions for model optimization, for sequence prediction and artificial sequences generation, context and pattern mining. The package is specifically adapted to the field of social sciences by allowing to learn VLMC models from sets of individual sequences possibly containing missing values and to account for case weights. The library also allows to fit segmented VLMC, where conditional transition probabilities are estimated and stored for each value of a covariate. This software results from research work executed within the framework of the Swiss National Centre of Competence in Research LIVES, which is financed by the Swiss National Science Foundation. The authors are grateful to the Swiss National Science Foundation for its financial support.

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