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Estimation from Censored Sample: Size-Biased Lomax Distribution

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Microelectronics, Electromagnetics and Telecommunications

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 655))

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Abstract

In this work, the scale parameter is derived with famous shape parameter from the censored sample victimization of the maximum likelihood technique for the size-biased Lomax distribution (SBLD). The predicting equations are changed to urge less-complicated and economical predictors. Two ways of modification are steered. The results are given.

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Author information

Authors and Affiliations

  1. Raghu Institute of Technology, Dakamarri, Visakhapatnam, 531162, India

    A. Naga Durgamamba

  2. DKS Post Graduate Institute and Research Center, Raipur, Chhattisgarh, 492001, India

    Kanti Sahu

Authors
  1. A. Naga Durgamamba
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  2. Kanti Sahu
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Corresponding author

Correspondence to A. Naga Durgamamba .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Raghu Institute of Technology, Visakhapatnam, Andhra Pradesh, India

    P. Satish Rama Chowdary

  2. Department of Electronics and Communication Engineering, Raghu Institute of Technology, Visakhapatnam, Andhra Pradesh, India

    V.V.S.S.S. Chakravarthy

  3. Department of Electronics and Telecommunication Engineering, Universitat Ramon Llull, Barcelona, Spain

    Jaume Anguera

  4. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  5. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

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Naga Durgamamba, A., Sahu, K. (2021). Estimation from Censored Sample: Size-Biased Lomax Distribution. In: Chowdary, P., Chakravarthy, V., Anguera, J., Satapathy, S., Bhateja, V. (eds) Microelectronics, Electromagnetics and Telecommunications. Lecture Notes in Electrical Engineering, vol 655. Springer, Singapore. https://doi.org/10.1007/978-981-15-3828-5_15

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  • DOI: https://doi.org/10.1007/978-981-15-3828-5_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3827-8

  • Online ISBN: 978-981-15-3828-5

  • eBook Packages: EngineeringEngineering (R0)

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