Diffusion approximation for nonparametric autoregression

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Abstract

A nonparametric statistical model of small diffusion type is compared with its discretization by a stochastic Euler difference scheme. It is shown that the discrete and continuous models are asymptotically equivalent in the sense of Le Cam's deficiency distance for statistical experiments, when the discretization step decreases with the noise intensity ε.

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Milstein, G., & Nussbaum, M. (1998). Diffusion approximation for nonparametric autoregression. Probability Theory and Related Fields, 112(4), 535–543. https://doi.org/10.1007/s004400050199

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