摘要翻译：
本文给出了一种计算隐马尔可夫模型状态序列中与模式相关的分布的方法，条件是观测全部或部分观测序列。概率是为非常一般的模式类（竞争模式和后来的推广模式）计算的，因此，该理论包括了一大类具有广泛应用的问题的特例结果。假定未观测状态序列是马尔可夫的，具有一般的依赖顺序。将辅助马尔可夫链与状态序列联系起来，用于简化计算。给出了两个实例来说明该方法的应用。第一个应用更多的是说明应用该理论的基本步骤，第二个是对DNA序列的更详细的应用，并表明该方法可以适应包括与生物学知识有关的限制。
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英文标题：
《Distributions associated with general runs and patterns in hidden Markov
  models》
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作者：
John A. D. Aston, Donald E. K. Martin
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最新提交年份：
2007
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Statistics        统计学
二级分类：Computation        计算
分类描述：Algorithms, Simulation, Visualization
算法、模拟、可视化
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英文摘要：
  This paper gives a method for computing distributions associated with patterns in the state sequence of a hidden Markov model, conditional on observing all or part of the observation sequence. Probabilities are computed for very general classes of patterns (competing patterns and generalized later patterns), and thus, the theory includes as special cases results for a large class of problems that have wide application. The unobserved state sequence is assumed to be Markovian with a general order of dependence. An auxiliary Markov chain is associated with the state sequence and is used to simplify the computations. Two examples are given to illustrate the use of the methodology. Whereas the first application is more to illustrate the basic steps in applying the theory, the second is a more detailed application to DNA sequences, and shows that the methods can be adapted to include restrictions related to biological knowledge.
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PDF链接：
https://arxiv.org/pdf/706.3985