Parameter estimation in stochastic differential equations
Author(s)
Bibliographic Information
Parameter estimation in stochastic differential equations
（Lecture notes in mathematics, 1923）
Springer, c2008
Available at / 59 libraries
-
Library, Research Institute for Mathematical Sciences, Kyoto University数研
L/N||LNM||1923200003619626
-
No Libraries matched.
- Remove all filters.
Note
Includes bibliographical references (p. [245]-261) and index
Description and Table of Contents
Description
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
Table of Contents
Continuous Sampling.- Parametric Stochastic Differential Equations.- Rates of Weak Convergence of Estimators in Homogeneous Diffusions.- Large Deviations of Estimators in Homogeneous Diffusions.- Local Asymptotic Mixed Normality for Nonhomogeneous Diffusions.- Bayes and Sequential Estimation in Stochastic PDEs.- Maximum Likelihood Estimation in Fractional Diffusions.- Discrete Sampling.- Approximate Maximum Likelihood Estimation in Nonhomogeneous Diffusions.- Rates of Weak Convergence of Estimators in the Ornstein-Uhlenbeck Process.- Local Asymptotic Normality for Discretely Observed Homogeneous Diffusions.- Estimating Function for Discretely Observed Homogeneous Diffusions.
by "Nielsen BookData"