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Minimum Variance Linear Unbiased Estimators and Predictors Based on Censored Samples

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Book cover An Introduction to Order Statistics

Part of the book series: Atlantis Studies in Probability and Statistics ((ATLANTISSPS,volume 3))

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Abstract

We consider the case, when some smallest and largest observations are missing. In this situation we construct the Minimum Variance Linear unbiased Estimators for location and scale parameters.

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Authors and Affiliations

  1. Department of Management Sciences, Rider University, Lawrenceville Road 2083, Lawrenceville, 08648, New Jersey, USA

    Mohammad Ahsanullah

  2. Department of Mathematics and Mechanics, St. Petersburg State University, St. Petersburg, 198904, c.St-Peterburg, Russia

    Valery Nevzorov

  3. Mathematics, Miami Dade College (Hialeah Campus), West 49th Street 1800, Miami, 33012, Florida, USA

    Mohammad Shakil

Authors
  1. Mohammad Ahsanullah
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  2. Valery Nevzorov
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  3. Mohammad Shakil
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Corresponding author

Correspondence to Mohammad Ahsanullah .

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© 2013 Atlantis Press

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Ahsanullah, M., Nevzorov, V., Shakil, M. (2013). Minimum Variance Linear Unbiased Estimators and Predictors Based on Censored Samples. In: An Introduction to Order Statistics. Atlantis Studies in Probability and Statistics, vol 3. Atlantis Press, Paris. https://doi.org/10.2991/978-94-91216-83-1_14

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