Self-normalized Cramer-type Moderate Deviations for Functionals of Markov Chain

Let{xn,n≥0}be a Markov chain with a countable state space S and let f(·)be a measurable function from S to R and consider the functionals of the Markov chain yn:=f(xn).We construct a new type of self-normalized sums based on the random-block scheme and establish a Crame′r-type moderate deviations for self-normalized sums of functionals of the Markov chain.     

Existence of Bayesian Estimates for the Polychotomous Quantal Response Models

This paper investigates the existence of Bayesian estimates for polychotomous quantal response models using a uniform improper prior distribution on the regression parameters. Necessary and sufficient conditions for the propriety of the posterior distribution with a general link function are established. In addition, the sufficient conditions for the existence of the posterior moments and the posterior moment generating function are obtained. It is also found that the propriety guarantees the existence of the maximum likelihood estimate.     

A non-uniform Berry–Esseen bound via Stein's method

This paper is part of our efforts to develop Stein's method beyond uniform bounds in normal approximation. Our main result is a proof for a non-uniform Berry–Esseen bound for independent and not necessarily identically distributed random variables without assuming the existence of third moments. It is proved by combining truncation with Stein's method and by taking the concentration inequality approach, improved and adapted for non-uniform bounds. To illustrate the technique, we give a proof for a uniform Berry–Esseen bound without assuming the existence of third moments. Received: 2 March 2000 / Revised version: 20 July 2000 / Published online: 26 April 2001     

独立不同分布部分和的增量有多小

Csrg和Révész(1981)对独立同分布随机变量部分和的增量有多小给出了一个十分漂亮的结果。但其证明恐有误。本文不仅修正了他们的错误,而且在更弱的条件下对独立不同分布序列得到了相应的结论。     

On a new law of the iterated logarithm of Erdős and Révész

Research supported by the Fok Yingtung Education Foundation and by an NSERC Canada Scientific Exchange Award at Carleton University, Ottawa, Canada.     

A note on small ball probability of a Gaussian process with stationary increments

Let {X(t), 0t1} be a Gaussian process with mean zero and stationary increments. Let ²(h) =EX ²(h) be nondecreasing and concave on (0,1). A sharp bound on the small ball probability ofX(·) is given in this paper.Research supported by Charles Phelps Taft Post-doctoral Fellowship of the University of Cincinnati and by the Fok Yingtung Education Foundation of China.     

Limit theorems for permutations of empirical processes with applications to change point analysis

Theorems of approximation of Gaussian processes for the sequential empirical process of the permutations of independent random variables are established. The results are applied to simulate critical values for the functionals of sequential empirical processes used in change point analysis. The proofs are based on the properties of rank statistics and negatively associated random variables.     

Self-normalized central limit theorem for sums of weakly dependent random variables

Let {X _n,n1} be a strictly stationary sequence of weakly dependent random variables satisfyingEX _n=,EX _n ² <,Var S _n /n² and the central limit theorem. This paper presents two estimators of ². Their weak and strong consistence as well as their rate of convergence are obtained for -mixing, -mixing and associated sequences.Supported by a NSF grant and a Taft travel grant. Department of Mathematical Sciences, University of Cincinnati, Cincinnati, Ohio 45221-0025.Supported by a Taft Post-doctoral Fellowship at the University of Cincinnati and by the Fok Yingtung Education Foundation of China. Hangzhou University, Hangzhou, Zhejiang, P.R. China and Department of Mathematics, National University of Singapore, Singapore 0511.     

Small Ball Estimates for Gaussian Processes under Sobolev Type Norms

A sharp small ball estimate under Sobolev type norms is obtained for certain Gaussian processes in general and for fractional Brownian motions in particular. New method using the techniques in large deviation theory is developed for small ball estimates. As an application the Chung's LIL for fractional Brownian motions is given in this setting.