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Statistical Inference for Middle Censored Data with Applications

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Applied Linear Algebra, Probability and Statistics

Part of the book series: Indian Statistical Institute Series ((INSIS))

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Abstract

In statistical literature, different censoring schemes have been widely studied and analysed. The focus has however been on right censored, left censored or doubly censored data. In this paper, we try to review the idea of “middle censoring”, which is relatively new but emerging. The sample observations are said to be middle censored if they fall inside a random interval. In this case, one can only observe the endpoints of the interval, rather than the actual data point. Over the last few years, there have been several papers outlining the statistical inference based on such middle censored data, which we survey here. These ideas include both parametric and non-parametric estimation strategies. We also support these techniques using relevant practical data examples for a better connect.

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Authors and Affiliations

  1. Indian Institute of Management, Indore, India

    Sudeep R. Bapat

Authors
  1. Sudeep R. Bapat
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Correspondence to Sudeep R. Bapat .

Editor information

Editors and Affiliations

  1. Indian Statistical Institute Delhi Center, New Delhi, India

    Ravindra B. Bapat

  2. Department of Data Science, CARAMS, Manipal Academy of Higher Education, Manipal, Karnataka, India

    Manjunatha Prasad Karantha

  3. Department of Mathematics, University of Manitoba, Winnipeg, MB, Canada

    Stephen J. Kirkland

  4. Indian Statistical Institute Delhi Center, New Delhi, India

    Samir Kumar Neogy

  5. Department of Mathematics, Indian Institute of Technology Guwahati, North Guwahati, Assam, India

    Sukanta Pati

  6. Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland

    Simo Puntanen

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R. Bapat, S. (2023). Statistical Inference for Middle Censored Data with Applications. In: Bapat, R.B., Karantha, M.P., Kirkland, S.J., Neogy, S.K., Pati, S., Puntanen, S. (eds) Applied Linear Algebra, Probability and Statistics. Indian Statistical Institute Series. Springer, Singapore. https://doi.org/10.1007/978-981-99-2310-6_15

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