IDEAS home Printed from https://ideas.repec.org/a/spr/sankha/v87y2025i2d10.1007_s13171-025-00383-z.html
   My bibliography  Save this article

A Neutrosophic Approach to the Minimum Variance Bound: Theory, Simulation, and Application

Author

Listed:
  • Muhammad Aslam

    (King Abdulaziz University)

Abstract

The minimum variance bound (MVB) is a key concept used to determine the minimum achievable variance for an estimator. However, a limitation of the traditional MVB under classical statistics is its applicability only to precise data. In reality, statistical data often contain imprecision, making the classical MVB less effective. This paper extends the MVB by incorporating neutrosophic statistics, which can account for uncertainty or indeterminacy in the data. We introduce the theory of the neutrosophic minimum variance bound (NMVB) and simulate its application using both normal and Poisson distributions. The simulation results demonstrate a significant difference between the MVB and NMVB. Additionally, we apply the NMVB to real-world data and observe that the MVB is sensitive to changes in sample size and the degree of indeterminacy.

Suggested Citation

  • Muhammad Aslam, 2025. "A Neutrosophic Approach to the Minimum Variance Bound: Theory, Simulation, and Application," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 87(2), pages 595-615, August.
    • Handle: RePEc:spr:sankha:v:87:y:2025:i:2:d:10.1007_s13171-025-00383-z
    DOI: 10.1007/s13171-025-00383-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13171-025-00383-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13171-025-00383-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Muhammad Aslam, 2022. "Neutrosophic F-Test for Two Counts of Data from the Poisson Distribution with Application in Climatology," Stats, MDPI, vol. 5(3), pages 1-11, August.
    2. Wen-Qi Duan & Zahid Khan & Muhammad Gulistan & Adnan Khurshid & Zeljko Stevic, 2021. "Neutrosophic Exponential Distribution: Modeling and Applications for Complex Data Analysis," Complexity, Hindawi, vol. 2021, pages 1-8, September.
    3. K. V. Harsha & Alladi Subramanyam, 2020. "Some information inequalities for statistical inference," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(5), pages 1237-1256, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Adnan Khurshid & Khalid Khan & Saleem Khan & Javier Cifuentes‐Faura, 2024. "Tackling sustainable development challenges: A fuzzy set examination of textile industry 4.0 and green supply chain barriers," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(6), pages 6819-6835, December.
    2. Yu MA & Adnan KHURSHID & Abdur RAUF & Jin ZHANG & Xinyu WANG & Claudia BOGHICEVICI, 2022. "Covid-19, Tourism and the Economy - Evidence from Pandemic Epicenters of Europe," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 65-82, April.
    3. Muhammad Aslam & Abdulrahman AlAita, 2025. "Neutrosophic Approach to Z-Testing for Poisson Count Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 87(1), pages 129-146, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sankha:v:87:y:2025:i:2:d:10.1007_s13171-025-00383-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.