IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v58y2009i2p197-210.html
   My bibliography  Save this article

M‐estimation of Boolean models for particle flow experiments

Author

Listed:
  • Jason A. Osborne
  • Tony E. Grift

Abstract

Summary. Probability models are proposed for passage time data collected in experiments with a device that was designed to measure particle flow during aerial application of fertilizer. Maximum likelihood estimation of flow intensity is reviewed for the simple linear Boolean model, which arises with the assumption that each particle requires the same known passage time. M‐estimation is developed for a generalization of the model in which passage times behave as a random sample from a distribution with a known mean. The generalized model improves the fit in these experiments. An estimator of total particle flow is constructed by conditioning on lengths of multiparticle clumps.

Suggested Citation

  • Jason A. Osborne & Tony E. Grift, 2009. "M‐estimation of Boolean models for particle flow experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(2), pages 197-210, May.
    • Handle: RePEc:bla:jorssc:v:58:y:2009:i:2:p:197-210
    DOI: 10.1111/j.1467-9876.2008.00655.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9876.2008.00655.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9876.2008.00655.x?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
    ---><---

    References listed on IDEAS

    as
    1. Catherine M. Crespi & William G. Cumberland & Sally Blower, 2005. "A Queueing Model for Chronic Recurrent Conditions under Panel Observation," Biometrics, The International Biometric Society, vol. 61(1), pages 193-198, March.
    2. Handley, John C., 2004. "Computationally efficient approximate likelihood procedures for the Boolean model," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 125-136, March.
    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. Catherine M. Crespi & Kenneth Lange, 2006. "Estimation for the Simple Linear Boolean Model," Methodology and Computing in Applied Probability, Springer, vol. 8(4), pages 559-571, December.
    2. Marc Chadeau‐Hyam & Paul S. Clarke & Chantal Guihenneuc‐Jouyaux & Simon N. Cousens & Robert G. Will & Azra C. Ghani, 2010. "An application of hidden Markov models to the French variant Creutzfeldt–Jakob disease epidemic," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(5), pages 839-853, November.
    3. Andrew C. Titman & Linda D. Sharples, 2010. "Semi-Markov Models with Phase-Type Sojourn Distributions," Biometrics, The International Biometric Society, vol. 66(3), pages 742-752, September.
    4. Crespi, Catherine M. & Boscardin, W. John, 2009. "Bayesian model checking for multivariate outcome data," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3765-3772, September.
    5. Na Cui & Yuguo Chen & Dylan S. Small, 2013. "Modeling Parasite Infection Dynamics when there Is Heterogeneity and Imperfect Detectability," Biometrics, The International Biometric Society, vol. 69(3), pages 683-692, September.

    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:58:y:2009:i:2:p:197-210. 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.