IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v54y2013i1p163-175.html
   My bibliography  Save this article

Updating a nonlinear discriminant function estimated from a mixture of two inverse Weibull distributions

Author

Listed:
  • K. Sultan
  • A. Al-Moisheer

Abstract

In this paper, we investigate the problem of updating a discriminant function on the basis of data of unknown origin. We consider the updating procedure for the nonlinear discriminant function on the basis of two inverse Weibull distributions in situations when the additional observations are mixed or classified. Then, we introduce the nonlinear discriminant function of the underlying model. Also, we calculate the total probabilities of misclassification. In addition, we investigate the performance of the updating procedures through series of simulation experiments by means of the relative efficiencies. Finally, we analyze a simulated data set by using the findings of the paper. Copyright Springer-Verlag 2013

Suggested Citation

  • K. Sultan & A. Al-Moisheer, 2013. "Updating a nonlinear discriminant function estimated from a mixture of two inverse Weibull distributions," Statistical Papers, Springer, vol. 54(1), pages 163-175, February.
    • Handle: RePEc:spr:stpapr:v:54:y:2013:i:1:p:163-175
    DOI: 10.1007/s00362-011-0416-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00362-011-0416-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00362-011-0416-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 search for a different version of it.

    References listed on IDEAS

    as
    1. Jose Ramon G. Albert & Laurence A. Baxter, 1995. "Applications of the Em Algorithm to the Analysis of Life Length Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(3), pages 323-341, September.
    2. Sultan, K.S. & Ismail, M.A. & Al-Moisheer, A.S., 2007. "Mixture of two inverse Weibull distributions: Properties and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5377-5387, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuebao Wang & Hui Xu & Dongya Cheng & Changjun Yu, 2018. "The local asymptotic estimation for the supremum of a random walk with generalized strong subexponential summands," Statistical Papers, Springer, vol. 59(1), pages 99-126, March.

    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. Nadeem Akhtar & Sajjad Ahmad Khan & Emad A. A. Ismail & Fuad A. Awwad & Akbar Ali Khan & Taza Gul & Haifa Alqahtani, 2024. "Analyzing quantitative performance: Bayesian estimation of 3-component mixture geometric distributions based on Kumaraswamy prior," Statistical Papers, Springer, vol. 65(7), pages 4431-4451, September.
    2. Chanseok Park & Min Wang, 2024. "Parameter Estimation of Birnbaum-Saunders Distribution under Competing Risks Using the Quantile Variant of the Expectation-Maximization Algorithm," Mathematics, MDPI, vol. 12(11), pages 1-17, June.
    3. Tian, Yuzhu & Zhu, Qianqian & Tian, Maozai, 2015. "Estimation for mixed exponential distributions under type-II progressively hybrid censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 85-96.
    4. Chang, Yiming & Tao, YinYing & Shan, Wei & Yu, Xiangyuan, 2023. "Forecasting COVID-19 new cases through the Mixed Generalized Inverse Weibull Distribution and time series model," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
    5. Almalki, Saad J. & Nadarajah, Saralees, 2014. "Modifications of the Weibull distribution: A review," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 32-55.
    6. Karl Mosler & Christoph Scheicher, 2008. "Homogeneity testing in a Weibull mixture model," Statistical Papers, Springer, vol. 49(2), pages 315-332, April.
    7. Felipe Gusmão & Edwin Ortega & Gauss Cordeiro, 2011. "The generalized inverse Weibull distribution," Statistical Papers, Springer, vol. 52(3), pages 591-619, August.
    8. Ye, Zhenggeng & Yang, Hui & Cai, Zhiqiang & Si, Shubin & Zhou, Fuli, 2021. "Performance evaluation of serial-parallel manufacturing systems based on the impact of heterogeneous feedstocks on machine degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    9. Tzong-Ru Tsai & Yuhlong Lio & Wei-Chen Ting, 2021. "EM Algorithm for Mixture Distributions Model with Type-I Hybrid Censoring Scheme," Mathematics, MDPI, vol. 9(19), pages 1-18, October.
    10. Kim, Jin Seon & Yum, Bong-Jin, 2008. "Selection between Weibull and lognormal distributions: A comparative simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 477-485, December.

    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:stpapr:v:54:y:2013:i:1:p:163-175. 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.