Maximum Likelihood Estimators: Numerical Simulations

Leonid I. Piterbarg and Alexander G. Ostrovskii
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Leonid I. Piterbarg: University of Southern California, Center for Applied Mathematical Sciences
Alexander G. Ostrovskii: Kyushu University, Research Institute for Applied Mechanics

Chapter Chapter 7 in Advection and Diffusion in Random Media, 1997, pp 145-177 from Springer

Abstract: 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.

Keywords: Numerical Experiment; Experimental Series; Diffusivity Estimate; Function Minimum; Forward Problem (search for similar items in EconPapers)
Date: 1997
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DOI: 10.1007/978-1-4757-4458-3_7

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