Projection pursuit is used to find interesting low-dimensional projections of high-dimensional data by optimizing an index over all possible projections. Most indexes have been developed to detect departure from known distributions, such as normality, or to find separations between known groups. Here, we are interested in finding projections revealing potentially complex bivariate patterns, using new indexes constructed from scagnostics and a maximum information coefficient, with a purpose to detect unusual relationships between model parameters describing physics phenomena. The performance of these indexes is examined with respect to ideal behaviour, using simulated data, and then applied to problems from gravitational wave astronomy. The implementation builds upon the projection pursuit tools available in the R package, tourr, with indexes constructed from code in the R packages, binostics, minerva and mbgraphic.

中文翻译：

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使用导览图直观地研究新的投影追踪指标的属性，并将其应用于物理问题

通过优化所有可能投影的索引，可以使用投影追踪来查找高维数据的有趣的低维投影。已经开发了大多数索引来检测与已知分布（例如正态分布）的偏离，或查找已知组之间的间隔。在这里，我们有兴趣寻找发现揭示潜在复杂双变量模式的预测，并使用根据诊断和最大信息系数构建的新指标来检测描述物理现象的模型参数之间的异常关系。使用模拟数据检查这些指标相对于理想行为的性能，然后将其应用于引力波天文学的问题。该实施基于R包，游览器，