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- W2005173637 abstract "In the present paper, a framework for parametric estimation in nonlinear time series is developed. Strong consistency and asymptotic normality of minimum Hellinger distance estimates for a determined class of nonlinear models are investigated. The main Interest for these estimates is motivated by their robustness under perturbations as it has been emphazized in Beran [2]. The first part of the paper is devoted to the study of some probabilistic properties which ensure the existence and the optimal properties of the estimates" @default.
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- W2005173637 date "1995-02-01" @default.
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- W2005173637 title "On the estimation of nonlinear time series models" @default.
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- W2005173637 doi "https://doi.org/10.1080/17442509508833972" @default.
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