High-dimensional Statistical Analysis and Its Application to an ALMA Map of NGC 253
Tsutomu T. Takeuchi,
Kazuyoshi Yata,
Kento Egashira
et al.
Abstract:In astronomy, if we denote the dimension of data as d and the number of samples as n, we often find a case with n ≪ d. Traditionally, such a situation is regarded as ill-posed, and there was no choice but to discard most of the information in data dimensions to let d < n. The data with n ≪ d is referred to as the high-dimensional low sample size (HDLSS). To deal with HDLSS problems, a method called high-dimensional statistics has rapidly developed in the last decade. In this work, we first introduce high-di… Show more
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