论文标题
seqroctm：一个MATLAB工具箱，用于分析由上下文树模型驱动的随机对象序列
SeqROCTM: A Matlab toolbox for the analysis of Sequence of Random Objects driven by Context Tree Models
论文作者
论文摘要
在几个研究问题中，我们涉及输入的概率序列（例如刺激序列），从中代理会产生相应的响应序列，并且可以对它们之间的关系进行建模。已经引入了一类新的随机过程，即\ textit {由上下文树模型驱动的随机对象的序列}，以在听觉统计学习的背景下对这种关系进行建模。本文介绍了一个免费可用的MATLAB工具箱（SEQROCTM），该工具箱实现了这一新类的随机过程和三个模型选择过程，以对其进行推断。此外，由于新数学框架与上下文树模型的密切关系，该工具箱还实现了上下文树模型的几种现有模型选择算法。
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.
