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We prove a central limit theorem for the components of the largest eigenvector of the adjacency matrix of a one-dimensional random dot product graph whose true latent positions are unknown. In particu...
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...
Under an appropriate regular variation condition, the affinely normalized partial sums of a sequence of independent and identically dis- tributed random variables converges weakly to a non-Gaussian ...
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.
On a limit theorem and invariance principle for symmetric statistics。

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