IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v49y2008i2p315-332.html
   My bibliography  Save this article

Homogeneity testing in a Weibull mixture model

Author

Listed:
  • Karl Mosler
  • Christoph Scheicher

Abstract

No abstract is available for this item.

Suggested Citation

  • Karl Mosler & Christoph Scheicher, 2008. "Homogeneity testing in a Weibull mixture model," Statistical Papers, Springer, vol. 49(2), pages 315-332, April.
  • Handle: RePEc:spr:stpapr:v:49:y:2008:i:2:p:315-332
    DOI: 10.1007/s00362-006-0015-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00362-006-0015-6
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s00362-006-0015-6?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. Charnigo R. & Sun J., 2004. "Testing Homogeneity in a Mixture Distribution via the L2 Distance Between Competing Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 488-498, January.
    2. Rodríguez Bernal, María Teresa, 2003. "Using weibull mixture distributions to model heterogeneous survival data," DES - Working Papers. Statistics and Econometrics. WS ws033208, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Hanfeng Chen & Jiahua Chen & John D. Kalbfleisch, 2001. "A modified likelihood ratio test for homogeneity in finite mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 19-29.
    4. 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.
    5. Wilfried Seidel & Karl Mosler & Manfred Alker, 2000. "A Cautionary Note on Likelihood Ratio Tests in Mixture Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(3), pages 481-487, September.
    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. Manuel Franco & Narayanaswamy Balakrishnan & Debasis Kundu & Juana-María Vivo, 2014. "Generalized mixtures of Weibull components," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 515-535, September.

    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. Meng Li & Sijia Xiang & Weixin Yao, 2016. "Robust estimation of the number of components for mixtures of linear regression models," Computational Statistics, Springer, vol. 31(4), pages 1539-1555, December.
    2. Garel, Bernard, 2007. "Recent asymptotic results in testing for mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5295-5304, July.
    3. Wong, Tony Siu Tung & Li, Wai Keung, 2014. "Test for homogeneity in gamma mixture models using likelihood ratio," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 127-137.
    4. Daeyoung Kim & Bruce Lindsay, 2015. "Empirical identifiability in finite mixture models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(4), pages 745-772, August.
    5. Ye, Mao & Lu, Zhao-Hua & Li, Yimei & Song, Xinyuan, 2019. "Finite mixture of varying coefficient model: Estimation and component selection," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 452-474.
    6. Zhu, Hongtu & Zhang, Heping, 2006. "Asymptotics for estimation and testing procedures under loss of identifiability," Journal of Multivariate Analysis, Elsevier, vol. 97(1), pages 19-45, January.
    7. Martin X. Dunbar & Hani M. Samawi & Robert Vogel & Lili Yu, 2014. "Steady-state Gibbs sampler estimation for lung cancer data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(5), pages 977-988, May.
    8. Andrew Sweeting, 2009. "The strategic timing incentives of commercial radio stations: An empirical analysis using multiple equilibria," RAND Journal of Economics, RAND Corporation, vol. 40(4), pages 710-742, December.
    9. 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.
    10. 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.
    11. Moming Li & Guoqing Diao & Jing Qin, 2020. "On symmetric semiparametric two‐sample problem," Biometrics, The International Biometric Society, vol. 76(4), pages 1216-1228, December.
    12. Hoshino Tadao & Yanagi Takahide, 2022. "Estimating marginal treatment effects under unobserved group heterogeneity," Journal of Causal Inference, De Gruyter, vol. 10(1), pages 197-216, January.
    13. Tran, Thanh N. & Wehrens, Ron & Buydens, Lutgarde M.C., 2006. "KNN-kernel density-based clustering for high-dimensional multivariate data," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 513-525, November.
    14. Derek S. Young & Xi Chen & Dilrukshi C. Hewage & Ricardo Nilo-Poyanco, 2019. "Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(4), pages 1053-1082, December.
    15. Markus Haas, 2004. "Mixed Normal Conditional Heteroskedasticity," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 211-250.
    16. Song Qin, Yong & Smith, Bruce, 2006. "The likelihood ratio test for homogeneity in bivariate normal mixtures," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 474-491, February.
    17. Lu, Zeng-Hua, 2009. "Covariate selection in mixture models with the censored response variable," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2710-2723, May.
    18. Martinez, M.J. & Lavergne, C. & Trottier, C., 2009. "A mixture model-based approach to the clustering of exponential repeated data," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 1938-1951, October.
    19. Juan Shen & Xuming He, 2015. "Inference for Subgroup Analysis With a Structured Logistic-Normal Mixture Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 303-312, March.
    20. Kasahara Hiroyuki & Shimotsu Katsumi, 2012. "Testing the Number of Components in Finite Mixture Models," Global COE Hi-Stat Discussion Paper Series gd12-259, Institute of Economic Research, Hitotsubashi University.

    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:49:y:2008:i:2:p:315-332. 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.