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.
翻译:在几个研究问题中,我们处理的是输入的概率序列(例如,刺激序列),一个代理商从中产生相应的响应序列,并有兴趣建模它们之间的关系。一种新的随机过程类别,即由上下文树模型驱动的随机物体的序列,已经引入了在听觉统计学习的背景下模拟这种关系。本文介绍了一个可自由使用的Matlab工具箱(SeqROCTM),用于实施这一新类型的随机过程和三个模型选择程序,以便对其作出推断。此外,由于新的数学框架与上下文树模型的密切关系,工具箱还实施了一些用于上下文树模型的现有模型选择算法。