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International Journal of Neutrosophic Science

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https://doi.org/10.54216/IJNS

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International Journal of Neutrosophic Science

Volume 21 , Issue 4 , PP: 72-83, 2023 | Cite this article as | XML | Html | PDF | Full Length Article

Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution

Sundus Naji Al-Aziz 1 * , Irsa Sajjad 2 , Javid Gani Dar 3 , Abd Al-Aziz H. EL Bagoury 4

  • 1 Department of Mathematical Sciences, Faculty of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia - (snalaziz@pnu.edu.sa)
  • 2 Department of mathematics and Statistics, Central South University, Changsha Hunan, China - (Irsasajjad@yahoo.com)
  • 3 Department of Applied Sciences, Symbiosis Institute of Technology, Symbiosis International (Deemed University) Pune, India - (javinfo.stat@yahoo.co.in)
  • 4 Higher Istitute of Engineering and Technology, Elmahala Elkobra, Egypt - (azizhel2013@yahoo.com)

    • Doi: https://doi.org/10.54216/IJNS.210408

    Received: February 16, 2023 Revised: May 21, 2023 Accepted: July 19, 2023
    Abstract

    In this research, we introduce a neutrosopic extension of the Ramous Louzada Distribution called the Inverse Ramous Louzada Distribution. We delve into several mathematical properties of this distribution, including the Survival function, Hazard Rate function, cumulative Hazard Rate function, and estimation technique. Moreover, we conduct a comparative analysis between the Inverse Weibull distribution and the traditional Ramous Louzada Distribution, which are two widely used distributions. Our aim is to assess the performance of the developed model through Maximum Likelihood Estimation (MLE), Standard Error (SE), and Goodness of Fit tests.

    Keywords :

    Survival Function , Hazard Rate Function , neutrosophic ramous Louzada Distribution , Maximum Likelihood Estimation.

    References

    [1] Khan, M. S. (2010). The beta inverse Weibull distribution. International Transactions in Mathematical Sciences and Computer, 3(1), 113-119.

    [2] Khan M. S., Pasha G. R. and Pasha A. H. (2008). Theoretical analysis of Inverse Weibull distribution. WSEAS Transactions on Mathematics, 7(2).

    [3] Khan M.S., Pasha G.R. and Pasha A.H. (2008). Fisher Information Matrix for the Inverse Weibull Distribution. IJMSEA, 2(III).

    [4] Khan, M. S., & King, R. (2012). Modified inverse Weibull distribution. Journal of statistics applications & Probability, 1(2), 115.

    [5] Khan, M. S. (2014). Modified inverse Rayleigh distribution. International Journal of Computer Applications, 87(13), 28-33.

    [6] Sundus Naji AL-Aziz, Expected Value of Asymmetric Coordinated Search Technique for Detecting a Randomly Located Target on the Plane, American Journal of Business and Operations Research, Vol. 6 , No. 1 , (2022) : 56-71 (Doi : https://doi.org/10.54216/AJBOR.060105).

    [7] Abd Al-Aziz Hosni El-Bagoury , Sundus Naji AL-Aziz , S.S.ASKAR, Social Spider Optimization Algorithm with Gradient Boosting Tree Model for Decision Making in Telemarketing Sector, American Journal of Business and Operations Research, Vol. 7 , No. 1 , (2022) : 09-18 (Doi : https://doi.org/10.54216/AJBOR.070101.

    [8] Sundus Naji AL-Aziz , Reem Atassi , Abd Al-Aziz Hosni El-Bagoury, Hybridization of Neutrosophic Logic with Quasi-Oppositional Chimp Optimization based Data Classification Model, International Journal of Neutrosophic Science, Vol. 18 , No. 3 , (2022) : 125-134 (Doi : https://doi.org/10.54216/IJNS.1803011).

    Cite This Article As :
    Naji, Sundus. , Sajjad, Irsa. , Gani, Javid. , Al-Aziz, Abd. Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution. International Journal of Neutrosophic Science, vol. , no. , 2023, pp. 72-83. DOI: https://doi.org/10.54216/IJNS.210408
    Naji, S. Sajjad, I. Gani, J. Al-Aziz, A. (2023). Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution. International Journal of Neutrosophic Science, (), 72-83. DOI: https://doi.org/10.54216/IJNS.210408
    Naji, Sundus. Sajjad, Irsa. Gani, Javid. Al-Aziz, Abd. Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution. International Journal of Neutrosophic Science , no. (2023): 72-83. DOI: https://doi.org/10.54216/IJNS.210408
    Naji, S. , Sajjad, I. , Gani, J. , Al-Aziz, A. (2023) . Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution. International Journal of Neutrosophic Science , () , 72-83 . DOI: https://doi.org/10.54216/IJNS.210408
    Naji S. , Sajjad I. , Gani J. , Al-Aziz A. [2023]. Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution. International Journal of Neutrosophic Science. (): 72-83. DOI: https://doi.org/10.54216/IJNS.210408
    Naji, S. Sajjad, I. Gani, J. Al-Aziz, A. "Advancing Covid-19 Data Modeling: Introducing a Neutrosophic Extension of Ramous Louzada Distribution," International Journal of Neutrosophic Science, vol. , no. , pp. 72-83, 2023. DOI: https://doi.org/10.54216/IJNS.210408

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