• DocumentCode
    1665641
  • Title

    Large deviations of consistent parameter estimates in diffusions

  • Author

    Levanony, David

  • Author_Institution
    Dept. of Electr. Eng., McGill Univ., Montreal, Que., Canada
  • Volume
    3
  • fYear
    1994
  • Firstpage
    2193
  • Abstract
    Rates of convergence of strongly consistent parameter estimates in diffusion processes are studied via large deviations (LD) laws for the suprema of the estimation error´s fail processes. First, conditional LD limits are obtained by utilizing a general martingale law. Those are then applied to derive simple stopping rules. Finally, unconditional LD lower bounds are derived by an extension of a well known direct method
  • Keywords
    convergence of numerical methods; diffusion; parameter estimation; probability; convergence rate; diffusion processes; large deviation laws; lower bounds; parameter estimation; probability; stopping rules; Convergence; Diffusion processes; Estimation error; Infinite horizon; Maximum likelihood estimation; Parameter estimation; Recursive estimation; Stochastic processes; Tail; Upper bound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on
  • Conference_Location
    Lake Buena Vista, FL
  • Print_ISBN
    0-7803-1968-0
  • Type

    conf

  • DOI
    10.1109/CDC.1994.411403
  • Filename
    411403