SeqROCTM: A Matlab toolbox for the analysis of Sequence of Random Objects driven by Context Tree Models

• URL: http://arxiv.org/abs/2009.06371v3
• Date: Thu, 22 Jul 2021 16:38:05 GMT
• Title: SeqROCTM: A Matlab toolbox for the analysis of Sequence of Random Objects driven by Context Tree Models
• Authors: Noslen Hern\'andez and Aline Duarte
• Abstract summary: A new class of processes, namely textitsequences of random objects driven by context tree models, has been introduced to model such relation in the context of auditory statistical learning. This paper introduces a freely available Matlab toolbox (SeqROCTM) that implements this new class of processes and three model selection procedures to make inference on it.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In several research problems we deal with probabilistic sequences of inputs (e.g., sequence of stimuli) from which an agent generates a corresponding sequence of responses and it is of interest to model the relation between them. A new class of stochastic processes, namely \textit{sequences of random objects driven by context tree models}, has been introduced to model such relation in the context of auditory statistical learning. This paper introduces a freely available Matlab toolbox (SeqROCTM) that implements this new class of stochastic processes and three model selection procedures to make inference on it. Besides, due to the close relation of the new mathematical framework with context tree models, the toolbox also implements several existing model selection algorithms for context tree models.

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