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Transformations for semi-continuous data

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  • Shmueli, Galit
  • Jank, Wolfgang
  • Hyde, Valerie

Abstract

Semi-continuous data arise in many applications where naturally-continuous data become contaminated by the data generating mechanism. The resulting data contain several values that are "too frequent", and in that sense are a hybrid between discrete and continuous data. The main problem is that standard statistical methods, which are geared towards continuous or discrete data, cannot be applied adequately to semi-continuous data. We propose a new set of two transformations for semi-continuous data that "iron out" the too-frequent values thereby transforming the data to completely continuous. We show that the transformed data maintain the properties of the original data, but are suitable for standard analysis. The transformations and their performance are illustrated using simulated data and real auction data from the online auction site eBay.

Suggested Citation

  • Shmueli, Galit & Jank, Wolfgang & Hyde, Valerie, 2008. "Transformations for semi-continuous data," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4000-4020, April.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:8:p:4000-4020
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    Cited by:

    1. Ahmed Zohair Djeddi & Ahmed Hafaifa & Abdellah Kouzou & Salam Abudura, 2017. "Exploration of reliability algorithms using modified Weibull distribution: application on gas turbine," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1885-1894, November.
    2. Wedad Elmaghraby & Wolfgang Jank & Shu Zhang & Itir Z. Karaesmen, 2015. "Sales Force Behavior, Pricing Information, and Pricing Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 495-510, October.

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