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We estimate linear functionals in the classical deconvolution problem by kernel esti-mators. We obtain a uniform central limit theorem with √n–rate on the assumption that the smoothness of the functio...
Adaptive and interacting Markov Chains Monte Carlo (MCMC) algorithms are a novel class of non-Markovian algorithms aimed at improving the simulation efficiency for complicated target distributions.
This article presents a statistical analysis method and intro- duces the corresponding software package tailstat,” which is believed to be widely applicable to today’s internet so- ciety. The prop...
Central Limit Theorem in D for breakdown processes。
This note gives the convergence rate in the central limit theorem and the random central limit theorem of some functions of the average of independent random variables.
Central limit theorem for some dependent random elements of D [0,1]。
We give tbe rate of convergence in the central limit theorem and the random central limit theorem for functions belonging to the class I of all real differentiable functions g such that gr E L(1).
The Levy and the Dudley metrics are used to give estimates of the rate convergence in the centrat- limit theorem for some functions of the average of independent random variables.
We obtain an almost sure convergence limit theorem for independent nonidentically distributed random variablcs. Lct S,, n 2 1, be the partial sums of independent random variables with zero means an...
A central limit theorem and a corresponding functional central h i t theorem are given under a uniform mixing condition for uniformly inf~tesimal triangular arrays of random variables which take va...

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