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Information Measures

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The Art of Progressive Censoring

Part of the book series: Statistics for Industry and Technology ((SIT))

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Abstract

Several information measures and corresponding expressions are presented for progressively censored samples. The discussion includes Fisher information, entropy, Kullback–Leibler information, Pitman closeness, and Tukey's linear sensitivity measure.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada

    N. Balakrishnan

  2. Institute of Statistics, RWTH Aachen University, Aachen, Germany

    Erhard Cramer

Authors
  1. N. Balakrishnan
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  2. Erhard Cramer
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Balakrishnan, N., Cramer, E. (2014). Information Measures. In: The Art of Progressive Censoring. Statistics for Industry and Technology. Birkhäuser, New York, NY. https://doi.org/10.1007/978-0-8176-4807-7_9

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