IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v62y2013i5p741-760.html
   My bibliography  Save this article

Smooth estimation of a lifetime distribution with competing risks by using regular interval observations: application to cocoa fruits growth

Author

Listed:
  • Patrice Takam Soh
  • Eugène-Patrice Ndong Nguéma
  • Henri Gwet
  • Michel Ndoumbè-Nkeng

Abstract

No abstract is available for this item.

Suggested Citation

  • Patrice Takam Soh & Eugène-Patrice Ndong Nguéma & Henri Gwet & Michel Ndoumbè-Nkeng, 2013. "Smooth estimation of a lifetime distribution with competing risks by using regular interval observations: application to cocoa fruits growth," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(5), pages 741-760, November.
    • Handle: RePEc:bla:jorssc:v:62:y:2013:i:5:p:741-760
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssc.12019
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Richard J. Cook & Leilei Zeng & Ker-Ai Lee, 2008. "A Multistate Model for Bivariate Interval-Censored Failure Time Data," Biometrics, The International Biometric Society, vol. 64(4), pages 1100-1109, December.
    2. Guadalupe Gomez & M. Luz Calle, 1999. "Non-parametric estimation with doubly censored data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(1), pages 45-58.
    3. Guadalupe Gómez & M. Calle & Ramon Oller, 2004. "Frequentist and Bayesian approaches for interval-censored data," Statistical Papers, Springer, vol. 45(2), pages 139-173, April.
    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. Pantazis, Nikos & Kenward, Michael G. & Touloumi, Giota, 2013. "Performance of parametric survival models under non-random interval censoring: A simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 16-30.
    2. Zapata, Samuel D. & Carpio, Carlos E., . "Distribution-Free Methods to Estimate Willingness to Pay Models Using Discrete Response Valuation Data," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 49(1).
    3. Zapata, Samuel D. & Carpio, Carlos E., 2014. "Distribution-free Methods for Estimation of Willingness to Pay Models Using Discrete Response Valuation Data," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170453, Agricultural and Applied Economics Association.
    4. Antonio Calcagnì & Luigi Lombardi & Lorenzo Avanzi & Eduardo Pascali, 2020. "Multiple mediation analysis for interval-valued data," Statistical Papers, Springer, vol. 61(1), pages 347-369, February.
    5. Chun Yin Lee & Kin Yau Wong & K. F. Lam & Jinfeng Xu, 2022. "Analysis of clustered interval‐censored data using a class of semiparametric partly linear frailty transformation models," Biometrics, The International Biometric Society, vol. 78(1), pages 165-178, March.
    6. Pao-sheng Shen, 2011. "Nonparametric estimation with doubly censored and truncated data," Computational Statistics, Springer, vol. 26(1), pages 145-157, March.
    7. Chen, Baojiang & Zhou, Xiao-Hua, 2013. "A correlated random effects model for non-homogeneous Markov processes with nonignorable missingness," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 1-13.
    8. Sabourin, Anne, 2015. "Semi-parametric modeling of excesses above high multivariate thresholds with censored data," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 126-146.
    9. Jialiang Li & Shuangge Ma, 2010. "Interval‐censored data with repeated measurements and a cured subgroup," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(4), pages 693-705, August.
    10. Qingning Zhou & Tao Hu & Jianguo Sun, 2017. "A Sieve Semiparametric Maximum Likelihood Approach for Regression Analysis of Bivariate Interval-Censored Failure Time Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 664-672, April.
    11. Zapata, Samuel D. & Carpio, Carlos E., 2016. "Non-Parametric Estimation of a Distribution Function with Interval Censored Data," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 229802, Southern Agricultural Economics Association.
    12. Lambert, Philippe, 2011. "Smooth semiparametric and nonparametric Bayesian estimation of bivariate densities from bivariate histogram data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 429-445, January.

    More about this item

    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:bla:jorssc:v:62:y:2013:i:5:p:741-760. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.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.