YGGDRASIL -用于学习分裂模型的统计软件包
YGGDRASIL - A Statistical Package for Learning Split Models
摘要：
本文件有两个主要目标。首先是为具有特定于上下文的独立结构的模型提供统计框架，即，条件独立性仅对条件变量的特定值成立。该框架由分裂模型类构成。分割模型是邻接表图形模型的扩展，允许比图形模型更复杂的建模。分裂模型的处理包括估计，表示和马尔可夫属性，用于读取在特定上下文中保持的那些独立性。第二个目标是介绍一个名为YGGDRASIL的软件包，它是为分裂模型中的统计推断而设计的，即，在数据的基础上学习这些模型。
英文摘要：
There are two main objectives of this paper. The first is to present a statistical framework for models with context specific independence structures, i.e., conditional independences holding only for sepcific values of the conditioning variables. This framework is constituted by the class of split models. Split models are extension of graphical models for contigency tables and allow for a more sophisticiated modelling than graphical models. The treatment of split models include estimation, representation and a Markov property for reading off those independencies holding in a specific context. The second objective is to present a software package named YGGDRASIL which is designed for statistical inference in split models, i.e., for learning such models on the basis of data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
