Central limit theorem for solutions of random initialized differential equations: a simple proof

Ileana Iribarren and José R. León

International Journal of Stochastic Analysis, 2006, vol. 2006, 1-20

Abstract:

We study the central and noncentral limit theorems for the convolution of a certain kernel h with F ( ξ ( ⋅ ) ) , where ξ is a stationary Gaussian process and F is a square integrable function with respect to the standard Gaussian measure. Our method consists in showing that in the weak dependence case, we can use the Lindeberg method, approaching the initial Gaussian process by an m -dependent process. We could say that only variance computations are needed to get the two types of limits. Then we apply the obtained results to the solutions of the certain differential equations.

Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnijsa:035206

DOI: 10.1155/JAMSA/2006/35206

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