Complete moment convergence of pairwise NQD random variables

It is known that the dependence structure of pairwise negative quadrant dependent (NQD) random variables is weaker than those of negatively associated random variables and negatively orthant dependent random variables. In this article, we investigate the moving average process which is based on the pairwise NQD random variables. The complete moment convergence and the integrability of the supremum are presented for this moving average process. The results imply complete convergence and the Marcinkiewicz–Zygmund-type strong law of large numbers for pairwise NQD sequences.     

鞅差序列滑动和过程的极限结果

该文获得了鞅差序列滑动和过程的完全收敛性, Marcinkiewicz-Zygmund强大数定律, 矩完全收敛性以及讨论了极大值矩的存在性问题, 推广和改进了已有的结果.     

Convergence rates for probabilities of moderate deviations for moving average processes

The present paper first shows that, without any dependent structure assumptions for a sequence of random variables, the refined results of the complete convergence for the sequence is equivalent to the corresponding complete moment convergence of the sequence. Then this paper investigates the convergence rates and refined convergence rates （or complete moment convergence） for probabilities of moderate deviations of moving average processes. The results in this paper extend and generalize some well-known results.     

On complete moment convergence of weighted sums for arrays of row-wise negatively associated random variables

Negatively associated (NA) random variables are a more general class of random variables which include a set of independent random variables and have been applied to many practical fields. In this paper, the complete moment convergence of weighted sums for arrays of row-wise NA random variables is investigated. Some sufficient conditions for complete moment convergence of weighted sums for arrays of row-wise NA random variables are established. Moreover, under the weaker conditions, we extend the results of Baek et al. [J. Korean Stat. Soc. 37 (2008), pp. 73–80] and Sung [Abstr. Appl. Anal. 2011 (2011)]. As an application, the complete moment convergence of moving average processes based on an NA random sequence is obtained, which improves the result of Li and Zhang [Stat. Probab. Lett. 70 (2004), pp. 191–197 ].     

Weighted least absolute deviations estimation for periodic ARMA models

This paper investigates the weighted least absolute deviations estimator (WLADE) for causal and invertible periodic autoregressive moving average (PARMA) models. Asymptotic normality of the estimator is derived under a fractional moment condition. A simulation study is given to assess the performance of the proposed WLADE.     

负相关样本平滑移动过程的矩完全收敛性(英文)

本文研究了负相关样本平滑移动过程Xk=∑∞i=-∞ai+kYi的矩完全收敛性,这里{Yi,-∞相似文献   

A law of large numbers result for a bifurcating process with an infinite moving average representation

This paper derives a law of large numbers theorem for bifurcating processes defined on a perfect binary tree. This theorem can be viewed as a generalization of some results that have already appeared in the literature. For instance, all that is required of the bifurcating process is an infinite moving average representation with geometrically decaying coefficients and a finite moment assumption. In addition, the summands are assumed to belong to a flexible class of functions that satisfy a generalized Lipschitz type condition. These two criteria allow for an expansive range of applicability. Two examples are given as corollaries to the theorem.     

A stopping rule for the Robbins-Monro method

A stopping rule for the multidimensional Robbins-Monro stochastic approximation method is developed in this paper. Both moving average and stationary -mixing type of correlated noise processes are treated. Sequentially determined confidence ellipsoids are constructed to fulfill the goal for the determination of the stopping rule. The limit behavior of the algorithm is investigated. It is shown that the stopped Robbins-Monro process is asymptotically normal. Such asymptotic normality is established by means of weak convergence methods.Communicated by Y. C. Ho     

鞅差时间序列半参数回归模型的小波估计

用小波方法研究了误差为滑动平均鞅差序列的半参数回归模型,得到了小波估计量的矩收敛速度及强收敛性.     

黄金分割算法在简支桥梁设计计算中的应用

移动荷载作用下,简支桥梁横截面上弯矩的变化为二元函数Z=f(x,y),本文给出了绝对最大弯矩Zm ax的极值点x*、y*的判别方法:利用数学中的黄金分割算法搜索梁的绝对最大弯矩对应的最危险横截面位置x*;利用力学中的影响线理论判别该截面发生最大弯矩时的最危险荷载位置y*,计算该横截面的最大弯矩得到梁的绝对最大弯矩.该算法易于编写计算程序,以计算机为工具,适用于任意有限多个平行移动荷载在桥梁上移动,对于桥梁的设计计算与安全评估,有一定的实用价值.     

An iterative least squares estimation algorithm for controlled moving average systems based on matrix decomposition

An iterative least squares parameter estimation algorithm is developed for controlled moving average systems based on matrix decomposition. The proposed algorithm avoids repeatedly computing the inverse of the data product moment matrix with large sizes at each iteration and has a high computational efficiency. A numerical example indicates that the proposed algorithm is effective.     

On convergence for sequences of pairwise negatively quadrant dependent random variables

In this paper, some new results on complete convergence and complete moment convergence for sequences of pairwise negatively quadrant dependent random variables are presented. These results improve the corresponding theorems of S.X.Gan, P.Y.Chen (2008) and H.Y. Liang, C. Su (1999).     

Long strange segments,ruin probabilities and the effect of memory on moving average processes

We obtain the rate of growth of long strange segments and the rate of decay of infinite horizon ruin probabilities for a class of infinite moving average processes with exponentially light tails. The rates are computed explicitly. We show that the rates are very similar to those of an i.i.d. process as long as the moving average coefficients decay fast enough. If they do not, then the rates are significantly different. This demonstrates the change in the length of memory in a moving average process associated with certain changes in the rate of decay of the coefficients.     

EWMA control charts for autoregressive processes

Many processes must be monitored by using observations that are correlated. An approach called algorithmic statistical process control can be employed in such situations. This involves fitting an autoregressive/moving average time series model to the data. Forecasts obtained from the model are used for active control, while the forecast errors are monitored by using a control chart. In this paper we consider using an exponentially weighted moving average (EWMA) chart for monitoring the residuals from an autoregressive model. We present a computational method for finding the out-of-control average run length (ARL) for such a control chart when the process mean shifts. As an application, we suggest a procedure and provide an example for finding the control limits of an EWMA chart for monitoring residuals from an autoregressive model that will provide an acceptable out-of-control ARL. A computer program for the needed calculations is provided via the World Wide Web.     

Lévy driven moving averages and semimartingales

The aim of the present paper is to study the semimartingale property of continuous time moving averages driven by Lévy processes. We provide necessary and sufficient conditions on the kernel for the moving average to be a semimartingale in the natural filtration of the Lévy process, and when this is the case we also provide a useful representation. Assuming that the driving Lévy process is of unbounded variation, we show that the moving average is a semimartingale if and only if the kernel is absolutely continuous with a density satisfying an integrability condition.     

A theoretical analysis of trading rules: an application to the moving average case with Markovian returns

A general framework for analysing trading rules is presented. We discuss different return concepts and different statistical processes for returns. We then concentrate on moving average trading rules and show, in the case of moving average models of length two, closed form expressions for the characteristic function of realized returns when the underlying return process follows a switching Markovian Gaussian process. An example is included which illustrates the technique.     

Asymptotic moving average representation of high-frequency sampled multivariate CARMA processes

High-frequency sampled multivariate continuous time autoregressive moving average processes are investigated. We obtain asymptotic expansion for the spectral density of the sampled MCARMA process \((Y_{n\varDelta })_{n \in {\mathbb {Z}}}\) as \(\varDelta \downarrow 0\), where \((Y_t)_{t \in {\mathbb {R}}}\) is an MCARMA process. We show that the properly filtered process is a vector moving average process, and determine the asymptotic moving average representation of it, thus generalizing the univariate results to the multivariate model. The determination of the moving average representation of the filtered process, important for the analysis of high-frequency data, is difficult for any fixed positive \(\varDelta \). However, the results established here provide a useful and insightful approximation when \(\varDelta \) is very small.     

A sharp inequality for martingales and its applications

In this paper, the best constant with respect to an inequality for martingales in Hall and Heyde (1980) is obtained. As a consequence, some large deviations with martingale difference and moving average process are established.     

监测Lévy稳定过程均值变点的平均运行时间估计

平均运行长度(时间)(ARL)是判断一控制图监测变点效果好坏的一个重要工具.本文主要研究Lévy稳定过程的均值变点监测问题.我们给出了三个控制图,即EWMA,GEWMA和GLR的ARL估计,并通过数值模拟比较了4个控制图监测均值变点的效果和差异.     

监测L\'{e}vy稳定过程均值变点的平均运行时间估计

平均运行长度(时间) (ARL)是判断一控制图监测变点效果好坏的一个重要工具\bd 本文主要研究L\'{e}vy 稳定过程的均值变点监测问题\bd 我们给出了三个控制图, 即EWMA, GEWMA和GLR的ARL 估计, 并通过数值模拟比较了4个控制图监测均值变点的效果和差异.