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Maximum Likelihood Estimators: Numerical Simulations

In: Advection and Diffusion in Random Media

Author

Listed:
  • Leonid I. Piterbarg

    (University of Southern California, Center for Applied Mathematical Sciences)

  • Alexander G. Ostrovskii

    (Kyushu University, Research Institute for Applied Mechanics)

Abstract

The theory presented in the previous chapter describes the behavior of the ML estimator only for a large number of observed modes. These asymptotic limits are too idealistic to be attained in reality. For this reason it is important to investigate numerically ML estimators under conditions where tracer data are limited in both time and space.

Suggested Citation

  • Leonid I. Piterbarg & Alexander G. Ostrovskii, 1997. "Maximum Likelihood Estimators: Numerical Simulations," Springer Books, in: Advection and Diffusion in Random Media, chapter 0, pages 145-177, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4757-4458-3_7
    DOI: 10.1007/978-1-4757-4458-3_7
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