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The Inverse Problem: Autoregressive Estimators

  • Leonid I. Piterbarg
  • Alexander G. Ostrovskii
Chapter

Abstract

Roughly speaking, all numerical solutions of linear partial differential equations can be broken down into two groups: (1) the expansion of the solution in terms of some basis (Galerkin method), and (2) the approximation of derivatives by finite differences. The same is relevant to the inverse problem.

Keywords

Gaussian Kernel Autoregressive Model Stochastic Partial Differential Equation Linear Partial Differential Equation Stochastic Partial Differential Equa 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • Leonid I. Piterbarg
    • 1
  • Alexander G. Ostrovskii
    • 2
  1. 1.Center for Applied Mathematical SciencesUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Research Institute for Applied MechanicsKyushu UniversityKasugaJapan

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