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Integrative Hypothesis Test and A5 Formulation: Sample Pairing Delta, Case Control Study, and Boundary Based Statistics

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Intelligence Science and Big Data Engineering (IScIDE 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8261))

Abstract

This paper continues the previous preliminary study on integrative hypothesis test (IHT) (Xu, LNCS7751, 2013). First, the coverage of IHT studies are elaborated from four aspects. Then, the previous preliminary A5 formulation for IHT is developed into one that integrates multiple individual tasks of discriminative analysis to improve hypothesis test with enhanced reliability. Next, a sample-pairing-delta based nonparametric statistics is proposed and its application to case control study is addressed. Moreover, a parametric separating boundary is further embedded into hypothesis test with statistics based on how far samples are away from the boundary, under which sample classification and hypothesis testing are coordinately implemented.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong

    Lei Xu

Authors
  1. Lei Xu
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Editor information

Editors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology, Xueyuan Road No. 30, 100083, Beijing, China

    Changyin Sun

  2. Department of Psychology, Peking University, Yiheyuan Road No. 5, 100871, Beijing, China

    Fang Fang

  3. Department of Computer Science and Technology, Nanjing University, Xianlin Avenue No. 163, 210023, Nanjing, China

    Zhi-Hua Zhou

  4. School of Automation, Southeast University, Sipailou No. 2, 210096, Nanjing, China

    Wankou Yang

  5. Institute of Automation, Chinese Academy of Sciences, No. 95 East Zhongguancun Road, 100190, Beijing, China

    Zhi-Yong Liu

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© 2013 Springer-Verlag Berlin Heidelberg

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Xu, L. (2013). Integrative Hypothesis Test and A5 Formulation: Sample Pairing Delta, Case Control Study, and Boundary Based Statistics. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_112

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  • DOI: https://doi.org/10.1007/978-3-642-42057-3_112

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42056-6

  • Online ISBN: 978-3-642-42057-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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