• DocumentCode
    2896651
  • Title

    Cramer-von Mises variance estimators for simulations

  • Author

    Goldsman, David ; Kang, Keebom ; Seila, Andrew F.

  • Author_Institution
    Sch. of Ind. & Syst. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • fYear
    1991
  • fDate
    8-11 Dec 1991
  • Firstpage
    916
  • Lastpage
    920
  • Abstract
    The authors study estimators for the variance parameter σ 2 of a stationary process. The estimators are based on weighted Cramer-von Mises statistics formed from the standardized time series of the process. Certain weightings yield estimators which are first-order unbiased for σ2 and which have low variance. It is also shown how the Cramer-von Mises estimators are related to the standardized time series area estimator; this relationship is used to establish additional estimators for σ2
  • Keywords
    parameter estimation; simulation; time series; Cramer-von Mises variance estimators; simulations; standardized time series; stationary process; time series area estimator; variance parameter; weighted Cramer-von Mises statistics; Statistical distributions; Stochastic processes; Sufficient conditions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference, 1991. Proceedings., Winter
  • Conference_Location
    Phoenix, AZ
  • Print_ISBN
    0-7803-0181-1
  • Type

    conf

  • DOI
    10.1109/WSC.1991.185705
  • Filename
    185705
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2896651