混合分数O-U过程的最小范数估计

本文研究混合分数O-U过程的最小范数估计问题.利用分数布朗运动驱动的随机微分方程偏差不等式,获得了混合分数O-U过程漂移参数的最小范数估计、相合性及渐近分布.     

非Lipschitz条件下混合型随机微分方程解的矩估计北大核心CSCD

本文的研究对象为非Lipschitz条件下混合分数布朗运动驱动的随机微分方程.混合分数布朗运动是布朗运动和分数布朗运动的线性组合.通过证明和混合分数布朗运动有关的伊藤公式,借助Malliavin积分理论,本文证明在非Lipschitz条件下,由混合分数布朗运动驱动的随机微分方程解的矩估计和连续性.     

随机删失下经验贝叶斯估计的渐近最优性

该文运用经验贝叶斯(empirical Bayes(简称EB))方法,在历史样本和当前样本均被另一个具有未知分布的变量随机右删失的条件下,构造了一个指数分布参数的经验贝叶斯估计并获得了它的渐近最优性．文章最后给出了一个例子和模拟结果．     

分数布朗运动驱动的脉冲中立型随机泛函微分方程的渐近稳定性

该文在实可分的Hilbert空间中,用不动点方法研究了由分数布朗运动驱动的脉冲中立型随机泛函微分方程温和解的P阶矩的渐近稳定性并举例说明所得结论的可行性.     

分数布朗运动模型的分维的估计方法(英文)

本文探讨分数布朗运动模型的分维的统计确定问题,给出几种新的估计方法．     

以分数布朗运动为输入过程的存储过程生成的上穿点过程

本文研究了以分数布朗运动为输入过程的存储过程上穿高水平u形成的点过程的渐近泊松特性,结果表明当分数布朗运动参数H∈(0,1/2),u→∞时,该点过程弱收敛到泊松过程.     

分数布朗运动随机微分方程的MLE和Bayes估计的大偏差不等式

本文研究了分数布朗运动随机微分方程未知参数的极大似然估计和Bayes估计的偏差不等式.在一定的正则条件下.利用似然方法给出了这两个估计量的大偏差不等式.     

以分数布朗运动为输入过程的存储过程生成的上穿点过程（英文）

本文研究了以分数布朗运动为输入过程的存储过程上穿高水平u形成的点过程的渐近泊松特性,结果表明当分数布朗运动参数H∈(0,1/2),u→∞时,该点过程弱收敛到泊松过程.     

分数布朗运动驱动下z一致连续的BSDE解的存在性与唯一性

本文研究一类由分数布朗运动驱动的一维倒向随机微分方程解的存在性与唯一性问题,在假设其生成元满足关于y Lipschitz连续,但关于z一致连续的条件下,通过应用分数布朗运动的Tanaka公式以及拟条件期望在一定条件下满足的单调性质,得到倒向随机微分方程的解的一个不等式估计,应用Gronwall不等式得到了一个关于这类方程的解的存在性与唯一性结果,推广了一些经典结果以及生成元满足一致Lipschitz条件下的由分数布朗运动驱动的倒向随机微分方程解的结果.     

基于马尔科夫和分数布朗运动具有扩散反应过程的随机基因调控网络模型

在考虑分数布朗运动,马尔可夫跳跃和时变时滞的扩散-反应过程的基础上建立了随机基因调控网络模型,通过构造Lyapunov函数,利用Wirtinger不等式和随机稳定性理论,时滞相关渐近稳定性定理,以推导线性矩阵不等式的形式实现了随机基因调控网络模型均方意义上的全局稳定性.     

Parametric estimation for linear stochastic differential equations driven by mixed fractional Brownian motion

ABSTRACT

We investigate the asymptotic properties of the maximum likelihood estimator and Bayes estimator of the drift parameter for stochastic processes satisfying linear stochastic differential equations driven by a mixed fractional Brownian motion. We obtain a Bernstein–von Mises-type theorem also for such a class of processes.     

Statistical Analysis of the Fractional Ornstein–Uhlenbeck Type Process

We consider the fractional analogue of the Ornstein–Uhlenbeck process, that is, the solution of a one-dimensional homogeneous linear stochastic differential equation driven by a fractional Brownian motion in place of the usual Brownian motion. The statistical problem of estimation of the drift and variance parameters is investigated on the basis of a semimartingale which generates the same filtration as the observed process. The asymptotic behaviour of the maximum likelihood estimator of the drift parameter is analyzed. Strong consistency is proved and explicit formulas for the asymptotic bias and mean square error are derived. Preparing for the analysis, a change of probability method is developed to compute the Laplace transform of a quadratic functional of some auxiliary process. This revised version was published online in August 2006 with corrections to the Cover Date.     

Information Inequalities for the Bayes Risk for a Family of Non-Regular Distributions

For a family of non-regular distributions with a location parameter including the uniform and truncated distributions, the stochastic expansion of the Bayes estimator is given and the asymptotic lower bound for the Bayes risk is obtained and shown to be sharp. Some examples are also given.     

Estimation of the bias parameter of the skew random walk and application to the skew Brownian motion

We study the asymptotic property of simple estimator of the parameter of a skew Brownian motion when one observes its positions on a fixed grid—or equivalently of a simple random walk with a bias at 0. This estimator, nothing more than the maximum likelihood estimator, is based only on the number of passages of the random walk at 0. It is very simple to set up, is consistent and is asymptotically mixed normal. We believe that this simplified framework is helpful to understand the asymptotic behavior of the maximum likelihood of the skew Brownian motion observed at discrete times which is studied in a companion paper.     

Parameter estimation for stochastic equations with additive fractional Brownian sheet

We study the maximum likelihood estimator for stochastic equations with additive fractional Brownian sheet. We use the Girsanov transform for the the two-parameter fractional Brownian motion, as well as the Malliavin calculus and Gaussian regularity theory.      

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In this article, using the limit theory of martingales, we study the moderate deviation for maximum likelihood estimator of unknown parameter in the stochastic partial differential equation driven by additive fractional Brownian motion with Hurst parameter, and the rate function can be calculated. Moreover, we apply our main result to several examples.     

Asymptotic Windings of Brownian Motion Paths on Riemann Surfaces

We study asymptotic winding properties of Brownian motion paths on Riemann surfaces by obtaining limit laws for stochastic line integrals along Brownian paths of meromorphic differential 1-forms (Abelian differentials).     

Instrumental variable estimation for a linear stochastic differential equation driven by a mixed fractional Brownian motion

We investigate the asymptotic properties of instrumental variable estimators of the drift parameter for stochastic processes satisfying linear stochastic differential equations driven by mixed fractional Brownian motion.     

Instrumental variable estimation for stochastic differential equations linear in drift parameter and driven by a sub-fractional Brownian motion

We investigate the asymptotic properties of instrumental variable estimators of the drift parameter for stochastic processes satisfying linear stochastic differential equations driven by a sub-fractional Brownian motion.