IDEAS home Printed from https://ideas.repec.org/a/ibn/ijspjl/v10y2021i4p77.html
   My bibliography  Save this article

Harris Extended Power Lomax Distribution: Properties, Inference and Applications

Author

Listed:
  • Adebisi Ade Ogunde
  • Victoria Eshomomoh Laoye
  • Ogbonnaya Nzie Ezichi
  • Kayode Oguntuase Balogun

Abstract

In this work, we present a five-parameter life time distribution called Harris power Lomax (HPL) distribution which is obtained by convoluting the Harris-G distribution and the Power Lomax distribution. When compared to the existing distributions, the new distribution exhibits a very flexible probability functions; which may be increasing, decreasing, J, and reversed J shapes been observed for the probability density and hazard rate functions. The structural properties of the new distribution are studied in detail which includes- moments, incomplete moment, Renyl entropy, order statistics, Bonferroni curve, and Lorenz curve etc. The HPL distribution parameters are estimated by using the method of maximum likelihood. Monte Carlo simulation was carried out to investigate the performance of MLEs. Aircraft wind shield data and Glass fibre data applications demonstrate the applicability of the proposed model.

Suggested Citation

  • Adebisi Ade Ogunde & Victoria Eshomomoh Laoye & Ogbonnaya Nzie Ezichi & Kayode Oguntuase Balogun, 2021. "Harris Extended Power Lomax Distribution: Properties, Inference and Applications," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(4), pages 1-77, July.
    • Handle: RePEc:ibn:ijspjl:v:10:y:2021:i:4:p:77
    as

    Download full text from publisher

    File URL: http://www.ccsenet.org/journal/index.php/ijsp/article/download/0/0/45482/48397
    Download Restriction: no
    File URL: http://www.ccsenet.org/journal/index.php/ijsp/article/view/0/45482
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richard L. Smith & J. C. Naylor, 1987. "A Comparison of Maximum Likelihood and Bayesian Estimators for the Three‐Parameter Weibull Distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(3), pages 358-369, November.
    2. Ahmad Alzaghal & Duha Hamed, 2019. "New Families of Generalized Lomax Distributions: Properties and Applications," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 8(6), pages 1-51, November.
    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. Rubio, F.J. & Steel, M.F.J., 2011. "Inference for grouped data with a truncated skew-Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3218-3231, December.
    2. Boikanyo Makubate & Fastel Chipepa & Broderick Oluyede & Peter O. Peter, 2021. "The Marshall-Olkin Half Logistic-G Family of Distributions With Applications," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(2), pages 120-120, March.
    3. Haitham M. Yousof & Yusra Tashkandy & Walid Emam & M. Masoom Ali & Mohamed Ibrahim, 2023. "A New Reciprocal Weibull Extension for Modeling Extreme Values with Risk Analysis under Insurance Data," Mathematics, MDPI, vol. 11(4), pages 1-26, February.
    4. A. A. Ogunde & S. T. Fayose & B. Ajayi & D. O. Omosigho, 2020. "Properties, Inference and Applications of Alpha Power Extended Inverted Weibull Distribution," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 9(6), pages 1-90, November.
    5. Mukhtar M. Salah & M. El-Morshedy & M. S. Eliwa & Haitham M. Yousof, 2020. "Expanded Fréchet Model: Mathematical Properties, Copula, Different Estimation Methods, Applications and Validation Testing," Mathematics, MDPI, vol. 8(11), pages 1-29, November.
    6. V. Filimonov & G. Demos & D. Sornette, 2017. "Modified profile likelihood inference and interval forecast of the burst of financial bubbles," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1167-1186, August.
    7. Yuanhua Feng & Wolfgang Karl Härdle, 2021. "Uni- and multivariate extensions of the sinh-arcsinh normal distribution applied to distributional regression," Working Papers CIE 142, Paderborn University, CIE Center for International Economics.
    8. Joarder, Avijit & Krishna, Hare & Kundu, Debasis, 2011. "Inferences on Weibull parameters with conventional type-I censoring," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 1-11, January.
    9. Hadeel Klakattawi & Dawlah Alsulami & Mervat Abd Elaal & Sanku Dey & Lamya Baharith, 2022. "A new generalized family of distributions based on combining Marshal-Olkin transformation with T-X family," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-29, February.
    10. Sandeep Kumar Maurya & Saralees Nadarajah, 2021. "Poisson Generated Family of Distributions: A Review," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 484-540, November.
    11. Hassan M. Okasha & Abdulkareem M. Basheer & A. H. El-Baz, 2021. "Marshall–Olkin Extended Inverse Weibull Distribution: Different Methods of Estimations," Annals of Data Science, Springer, vol. 8(4), pages 769-784, December.
    12. Acitas, Sukru & Aladag, Cagdas Hakan & Senoglu, Birdal, 2019. "A new approach for estimating the parameters of Weibull distribution via particle swarm optimization: An application to the strengths of glass fibre data," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 116-127.
    13. Ahtasham Gul & Muhammad Mohsin & Muhammad Adil & Mansoor Ali, 2021. "A modified truncated distribution for modeling the heavy tail, engineering and environmental sciences data," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-24, April.
    14. Abdulrahman Abouammoh & Mohamed Kayid, 2020. "A New Family of Extended Lindley Models: Properties, Estimation and Applications," Mathematics, MDPI, vol. 8(12), pages 1-13, December.
    15. Duha Hamed & Ahmad Alzaghal, 2021. "New class of Lindley distributions: properties and applications," Journal of Statistical Distributions and Applications, Springer, vol. 8(1), pages 1-22, December.
    16. Shahram Yaghoobzadeh, 2017. "A new generalization of the Marshall–Olkin Gompertz distribution," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1580-1587, November.
    17. Ashish Kumar Shukla & Sakshi Soni & Kapil Kumar, 2023. "An inferential analysis for the Weibull-G family of distributions under progressively censored data," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1488-1524, September.
    18. Morais, Alice Lemos & Barreto-Souza, Wagner, 2011. "A compound class of Weibull and power series distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1410-1425, March.
    19. Haitham M. Yousof & Hafida Goual & Walid Emam & Yusra Tashkandy & Morad Alizadeh & M. Masoom Ali & Mohamed Ibrahim, 2023. "An Alternative Model for Describing the Reliability Data: Applications, Assessment, and Goodness-of-Fit Validation Testing," Mathematics, MDPI, vol. 11(6), pages 1-26, March.
    20. Maha A Aldahlan & Farrukh Jamal & Christophe Chesneau & Ibrahim Elbatal & Mohammed Elgarhy, 2020. "Exponentiated power generalized Weibull power series family of distributions: Properties, estimation and applications," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-25, March.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:ijspjl:v:10:y:2021:i:4:p:77. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.