Modeling and replicating statistical topology and evidence for CMB nonhomogeneity.

ABSTRACT: Under the banner of "big data," the detection and classification of structure in extremely large, high-dimensional, data sets are two of the central statistical challenges of our times. Among the most intriguing new approaches to this challenge is "TDA," or "topological data analysis," one of the primary aims of which is providing nonmetric, but topologically informative, preanalyses of data which make later, more quantitative, analyses feasible. While TDA rests on strong mathematical foundations from topology, in applications, it has faced challenges due to difficulties in handling issues of statistical reliability and robustness, often leading to an inability to make scientific claims with verifiable levels of statistical confidence. We propose a methodology for the parametric representa

SUBMITTER: Adler RJ 

PROVIDER: S-EPMC5692542 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature