• DocumentCode
    2568473
  • Title

    The bioequivalence identification based on the situ data

  • Author

    Wang, Tie ; Lin, Jianyang ; Chen, Zhiguang

  • Author_Institution
    Sch. of Vehicle & Traffic, Shenyang Ligong Univ., Shenyang
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    4317
  • Lastpage
    4321
  • Abstract
    To the traditional bioequivalent identification, the stringent requirements, limitations on the scope of inspection and the enormous waste of inspection resources are analyzed. The bioequivalent model of normal distribution is established perfectly by using statistical theory; the normal model of tested system about medium-sized samples is established by using information entropy method of no-statistics theory, the normal model of tested system about small-sized samples is established by using Bayesian method of no-statistics theory. In order to achieve the unified identification algorithm, the equivalent normal transforms of information distribution is quoted; all models are established and are calculated through VB Programming; Through analysis of the examples about traditional and normal method, we know that two bioequivalent identification methods is identity, but normal method is more simple, intuitive and easy to grasp than traditional method. The normal bioequivalent method can suit to broad and complex bioequivalence test, save various testing resources, reduce testing costs.
  • Keywords
    Bayes methods; normal distribution; sampling methods; statistical testing; Bayesian method; VB programming; bioequivalence identification; bioequivalence tests; information entropy method; medium-sized samples; no-statistics theory; normal distribution; situ data; statistical theory; Algorithm design and analysis; Bayesian methods; Costs; Gaussian distribution; Information analysis; Information entropy; Inspection; System testing; Bayes; Equivalent; Information entropy; Mathematics model; Situ data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4598145
  • Filename
    4598145