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Stochastic simulators such as Monte-Carlo estimators are widely used in science and engineering to study physical systems through their probabilistic representation. Global sensitivity analysis aims t...
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
In this paper we considered a general seasonal time series model with K-dependent and \rambda-dependent errors, which are new concepts of dependence. In this model we derived consistency and asymptoti...
In nonparametric classification and regression problems, support vector machines (SVMs) attract much attention in theoretical and in applied statistics. In an abstract sense, SVMs can be seen as regu...
Wc mnf;i&r the paablem of density estimation for m a one-sided linear prosees X, = zt _ , a, Z, , with i.id square iategra- Me kovatims - We prove that under weak contritions on (ai)&, which imply ...
Asymptotic Normality of Estimates for a Class of Stochastic Epidemic Models。

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