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This article proposes a new information-based subdata selection (IBOSS) algorithm, Squared Scaled Distance Algorithm (SSDA). It is based on the invariance of the determinant of the information matrix under orthogonal

This article proposes a new information-based subdata selection (IBOSS) algorithm, Squared Scaled Distance Algorithm (SSDA). It is based on the invariance of the determinant of the information matrix under orthogonal transformations, especially rotations. Extensive simulation results show that the new IBOSS algorithm retains nice asymptotic properties of IBOSS and gives a larger determinant of the subdata information matrix. It has the same order of time complexity as the D-optimal IBOSS algorithm.

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    Date Created
    • 2017
    Resource Type
  • Text
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    • Partial requirement for: M.S., Arizona State University, 2017
      Note type
      thesis
    • Includes bibliographical references (page 40)
      Note type
      bibliography
    • Field of study: Statistics

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    by Yi Zheng

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