English  |  正體中文  |  简体中文  |  Items with full text/Total items : 55241/89544 (62%)
Visitors : 10729901      Online Users : 31
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41349


    Title: Bayesian nonparametrics for compliance to exposure standards
    Authors: Symons, Michael J.;陳主智;Chen, Chu-chih;Flynn, Michael R.
    Contributors: 淡江大學數學學系
    Keywords: Nuisance parameters;Predictive distributions
    Date: 1993-12
    Issue Date: 2010-01-28 07:21:40 (UTC+8)
    Publisher: American Statistical Association
    Abstract: A Bayesian nonparametric view of compliance to occupational standards is achieved through predictive distributions. The common assumption of lognormality of environmental exposures is relaxed while recognizing the practicality of a finite number of possible samples. These probability of compliance calculations are conditional on observing some of the samples. Familiar binomial and normal modes are identified with the classical perspective as limits of Bayesian nonparametric and parametric strategies, when the number of observed samples increases. In this situation, extensive previous sample data provide a correspondence between the classical and Bayesian approaches, rather than little or no previous information. Using an example, alternative procedures are illustrated and compared. Currently used methodology can be anti-conservative for protecting employees.
    Relation: Journal of the American Statistical Association 88(424), pp.1237-1241
    DOI: 
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

    Files in This Item:

    File Description SizeFormat
    0KbUnknown264View/Open
    index.html0KbHTML79View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback