Fan, J.Q. and Yao, Q.W. and Tong, H. (1996) Estimation of conditional densities and sensitivity measures in nonlinear dynamical systems. Biometrika, 83 (1). pp. 189-206. ISSN 0006-3444.
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Using locally polynomial regression, we develop nonparametric estimators for the conditional density function and its square root, and their partial derivatives. Two measures of sensitivity to initial conditions in nonlinear stochastic dynamic systems are proposed, one of which relates Fisher information with initial-value sensitivity in dynamical systems. We propose estimators for these, and show asymptotic normality for one of them. We further propose a simple method for choosing the bandwidth. The methods are illustrated by simulation of two well-known models in dynamical systems.
|Uncontrolled keywords:||conditional density function; Kullback-Leibler information; locally polynomial regression; nonlinear time series; sensitivity to initial values|
|Subjects:||Q Science > QA Mathematics (inc Computing science)|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science|
|Depositing User:||R.F. Xu|
|Date Deposited:||09 Jun 2009 14:08|
|Last Modified:||09 Jun 2009 14:08|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/19170 (The current URI for this page, for reference purposes)|
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