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Estimating the Distribution Function Using Parametric Methods in Informative Model of Random Censorship from Both Sides

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Information Technologies and Mathematical Modelling. Queueing Theory and Applications (ITMM 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1803))

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Abstract

This paper focuses on the investigation of two semi-parametric estimators for distribution functions in an informative model of random censorship from both sides. During the investigation of these estimators, we utilized the characterization properties of the informative model to gather insights. Additionally, we discussed the properties of these estimators using numerical modeling methods.

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Author information

Authors and Affiliations

  1. Moscow State University, Tashkent Branch, Tashkent, Uzbekistan

    Abdushukurov Abdurakhim Akhmedovich

  2. Navoi State Pedagogical Institute, Navoi, Uzbekistan

    Mansurov Dilshod Ravilovich

Authors
  1. Abdushukurov Abdurakhim Akhmedovich
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  2. Mansurov Dilshod Ravilovich
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Corresponding author

Correspondence to Mansurov Dilshod Ravilovich .

Editor information

Editors and Affiliations

  1. Belarusian State University, Minsk, Belarus

    Alexander Dudin

  2. Tomsk State University, Tomsk, Russia

    Anatoly Nazarov

  3. Tomsk State University, Tomsk, Russia

    Alexander Moiseev

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Akhmedovich, A.A., Ravilovich, M.D. (2023). Estimating the Distribution Function Using Parametric Methods in Informative Model of Random Censorship from Both Sides. In: Dudin, A., Nazarov, A., Moiseev, A. (eds) Information Technologies and Mathematical Modelling. Queueing Theory and Applications. ITMM 2022. Communications in Computer and Information Science, vol 1803. Springer, Cham. https://doi.org/10.1007/978-3-031-32990-6_19

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  • DOI: https://doi.org/10.1007/978-3-031-32990-6_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-32989-0

  • Online ISBN: 978-3-031-32990-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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