• DocumentCode
    1129459
  • Title

    Single-run gradient estimation via measure-valued differentiation

  • Author

    Heidergott, Bernd ; Hordijk, Arie

  • Author_Institution
    Tinbergen Inst., Vrije Univ. Amsterdam, Netherlands
  • Volume
    49
  • Issue
    10
  • fYear
    2004
  • Firstpage
    1843
  • Lastpage
    1847
  • Abstract
    We show how single-run-based measure-valued differentiation gradient estimators can be obtained. The key idea is to apply a change of measure a posterior to the mathematical analysis of the derivative. From the point of view of the likelihood ratio method, we show that likelihood ratio type gradient estimators can be applied in situations where the mathematical conditions needed for applying a likelihood ratio analysis are not met.
  • Keywords
    Markov processes; differentiation; gradient methods; maximum likelihood estimation; Markov chains; likelihood ratio method; measure-valued differentiation; single-run gradient estimation; Density measurement; Imaging phantoms; Kernel; Mathematical analysis; State estimation; Stochastic systems; Sufficient conditions; Telecommunication computing; Transportation; Virtual manufacturing; Gradient estimation; Markov chains; likelihood ratios; measure-valued differentiation;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2004.835588
  • Filename
    1341589
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1129459