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On the Typology of Relations

机译:论关系的类型学

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The possibility of undertaking matrix/optimization-free cladistic analysis is one of the most interesting ideas to emerge in the last few decades from within the field of systematics, particularly in the development of cladistics. The purpose of this paper is to design further opportunities and prospects made possible by eliminating the matrix as the primary source of data representation. The main focus of this paper is to outline a supertree approach that, if combined with the methodology of three-taxon statement analysis (3TA), may be seen as a powerful heuristic alternative to the application of conventional matrix/optimization-based methods used for the analysis of systematic data, and which currently forms the mainstream of contemporary phylogenetics. Using the average consensus technique as an example, we demonstrate explicitly that methods of construction of supertrees may be applied to the array of three-taxon statements (3TS), especially if the latter are represented initially as minimal trees, not as binary matrices, as was originally proposed. The 3TA-average consensus procedure recognizes solely reversal'-based clades and is also free from the potential issues of 3TA, such as the data distortion due to inability to handle putative reversals. Thus the main benefit of this new approach over the traditional one is its accuracy and advantages when implementing the Hennigian views on the cladistic analysis that states that all characters must be a priori polarized before the best fitting tree is found. We also found that the average consensus technique (as well as other median supertree calculation techniques) is purely typological and we stressed that this simple point had never been mentioned before. We proposed that the average consensus of 3TSs (as well as any median consensus of 3TSs) may be viewed as a median type and the extended procedure of the traditional 3TA may be treated as a typology of the relations. The connection between median type and phylo
机译:进行无矩阵/无优化的分支分析的可能性是过去几十年来系统学领域出现的最有趣的想法之一,特别是在分支学的发展中。本文的目的是通过消除矩阵作为数据表示的主要来源来设计更多的机会和前景。本文的主要重点是概述一种超树方法,如果与三分类群陈述分析(3TA)的方法相结合,可以被视为一种强大的启发式替代方案,可以替代用于分析系统数据的传统基于矩阵/优化的方法的应用,目前构成了当代系统发育学的主流。以平均共识技术为例,我们明确地证明了超级树的构造方法可以应用于三分类群语句(3TS)的数组,特别是如果后者最初表示为最小树,而不是最初提出的二进制矩阵。3TA 平均共识程序仅识别基于反转的分支,并且也没有 3TA 的潜在问题,例如由于无法处理假定的反转而导致的数据失真。因此,与传统方法相比,这种新方法的主要优点是,在实施亨尼格式关于分支分析的观点时,它的准确性和优势,即在找到最合适的树之前,所有字符都必须先验极化。我们还发现,平均共识技术(以及其他中位数超树计算技术)纯粹是类型学的,我们强调这个简单的点以前从未被提及过。我们提出,3TS的平均共识(以及3TS的任何中位数共识)可以被视为中位数类型,而传统3TA的扩展过程可以被视为关系的类型学。中位类型与门之间的联系

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