Discriminant analysis for dynamics of stable processes

Motoyoshi Nishikawa, Masanobu Taniguchi*

*この研究の対応する著者

研究成果: Article査読

1 被引用数 (Scopus)

抄録

We consider the problem of classifying an α-stable linear process into two categories described by two hypotheses π1 and π2. These hypotheses are specified by the "normalized power transfer functions" over(f, ̃) (λ) and over(g, ̃) (λ) under π1 and π2, respectively. In this paper, we suggest a classification statistic In (over(f, ̃), over(g, ̃)) based on the normalized power transfer functions. We show that In (over(f, ̃), over(g, ̃)) is a consistent classification criterion in the sense that the misclassification probabilities converge to zero as the sample size tends to infinity. When over(g, ̃) (λ) is contiguous to over(f, ̃) (λ), we also evaluate the goodness of fit of In (over(f, ̃), over(g, ̃)) in terms of the misclassification probabilities. Our results have potential applications in various fields, e.g., credit rating in finance, and so on. Several numerical examples will be given.

本文言語English
ページ(範囲)82-96
ページ数15
ジャーナルStatistical Methodology
6
1
DOI
出版ステータスPublished - 2009 1月 1

ASJC Scopus subject areas

  • 統計学および確率

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