Titlebook: Data Analysis and Rationality in a Complex World; Theodore Chadjipadelis,Berthold Lausen,Rebecca Nug Conference proceedings 2021 Springer

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Measuring and Testing Mutual Dependence for Functional Data,In this paper, measures of mutual independence of many-vector random processes were defined. Based on these measures, permutation tests of mutual independence of these random processes were also given. The properties of the described methods were presented using simulation studies for univariate and multivariate processes.

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Richard L. Frock,Jiazhi Hu,Frederick W. Altearning algorithm is designed to consider two potentially error-prone sources of information associated with the same observations. One reflects dissimilarities in the “feature space” and the other the temporal (resp. spatial) constraint structure between the observations. A distance-based approach

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https://doi.org/10.1007/978-3-662-06255-5re of our analysis are both the priorities of the national parties campaigning for the 2019 European elections and the manifestos of the transnational party groups, each consisting of national member parties from the 28 member states of the European Union. By comparing the major priorities of nation

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B. Rommel,J. Bullerdiek,W. Schlootmon approach is to use internal validity criteria. For mixtures of linear regressions whose parameters are estimated via the maximum likelihood approach, we propose a three-term decomposition of the total sum of squares as a starting point to define some internal validity criteria. Exploiting this d

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Kurt Benirschke,T. C. Hsu,Robert N. Shoffnersimilarity measures for unconventional fuzzy numbers, i.e. asymmetric, overlapping triangular, with unequal width. Resulting distance measures are to be used for clustering and linear ordering of objects. The method applied consists of an attempt to identify and to discuss the applicability of speci

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