Complete moment convergence of moving-average process generated by a class of random variables

In this article, we establish the complete moment convergence of a moving-average process generated by a class of random variables satisfying the Rosenthal-type maximal inequality and the week mean dominating condition. On the one hand, we give the correct proof for the case p = 1 in Ko (2015 Ko, M.H. (2015). Complete moment convergence of moving average process generated by a class of random variables. J. Inequalities Appl. 2015(1):1–9. Article ID 225.[Crossref], [Web of Science ®] , [Google Scholar]); on the other hand, we also consider the case αp = 1 which was not considered in Ko (2015 Ko, M.H. (2015). Complete moment convergence of moving average process generated by a class of random variables. J. Inequalities Appl. 2015(1):1–9. Article ID 225.[Crossref], [Web of Science ®] , [Google Scholar]). The results obtained in this article generalize some corresponding ones for some dependent sequences.     

基于机会成本投资决策分析方法的新思考

项目投资决策应基于资金的机会成本进行贴现分析,但对什么是资金的机会成本却存在不同理解,从而导致投资决策错误。本文明确提出应以行业基准收益率作为资金的机会成本的度量,以净现值最大化为准则科学地评价投资项目的经济效益。     

基于MODWT的FIGARCH模型波动的持续性与相关性

基于FIGARCH模型与最大重复离散小波变换的小波多分辨分析,提出了不同尺度下的FIGARCH模型,并以此来讨论金融波动序列在不同尺度下的持续性问题;利用可描述两列波动序列的整体相关特性的交叉互相关函数,提出了可以描述两列波动序列在不同尺度、不同滞后期下小波交叉互相关函数的定义,并进行了实证分析。     

Distance-based outlier detection for high dimension,low sample size data

Despite the popularity of high dimension, low sample size data analysis, there has not been enough attention to the sample integrity issue, in particular, a possibility of outliers in the data. A new outlier detection procedure for data with much larger dimensionality than the sample size is presented. The proposed method is motivated by asymptotic properties of high-dimensional distance measures. Empirical studies suggest that high-dimensional outlier detection is more likely to suffer from a swamping effect rather than a masking effect, thus yields more false positives than false negatives. We compare the proposed approaches with existing methods using simulated data from various population settings. A real data example is presented with a consideration on the implication of found outliers.     

The random partition masking model for interval-censored and masked competing risks data

We study the nonparametric maximum likelihood estimate (NPMLE) of the cdf or sub-distribution functions of the failure time for the failure causes in a series system. The study is motivated by a cancer research data (from the Memorial Sloan-Kettering Cancer Center) with interval-censored time and masked failure cause. The NPMLE based on this data set suggests that the existing masking models are not appropriate. We propose a new model called the random partition masking model, which does not rely on the commonly used symmetry assumption (namely, given the failure cause, the probability of observing the masked failure causes is independent of the failure time; see Flehinger et al. Inference about defects in the presence of masking, Technometrics 38 (1996), pp. 247–255). The RPM model is easier to implement in simulation studies than the existing models. We discuss the algorithms for computing the NPMLE and study its asymptotic properties. Our simulation and data analysis indicate that the NPMLE is feasible for a moderate sample size.     

Reliability of semi-Markov missions

We consider a device that is designed to perform missions consisting of a random sequence of phases or stages with random durations. The mission process is described by a Markov renewal process and the system is a complex one consisting of a number of components whose lifetimes depend on the phases of the mission. We discuss models and tools to compute system, mission, and phase reliabilities using Markov renewal theory. A simplified model involving a mission-based system with maximal repair is analyzed first, and the results are then extended to the case where there is no repair using intrinsic aging concepts. Our objective is to focus on computation of system reliability for these two possible extreme cases.     

On the maximal invariance of manova step down procedure statistics

Subbaiah and Mudhol kar (1978) remark the general mu1tivariate linear hypothesis testing step down procedure statistics do not appear to be maximal invariants under nonsingular lower triangular matrix transformations of the original variates. This paper proves the maximal invariance of these statistics. The invariance results are essential to study the power functions of the step down procedures for MANOVA problems. An example is given to show that such power function studies are very involved.     

有氧训练在体育教学中的运用

通过对本科二年级学生武术选项课近一学年的教学改革实验 ,按照有氧训练的原则安排课的生理负荷量 ,使学生的氧运输系统的能力得到很大的提高 ,VO2 max、最大负荷、氧脉搏较实验前有明显提高 ;VO2 max与最大负荷及心电RV5电压高度相关 ,反映出有氧能力与人体运动和心肺系统的内在联系 ,达到了改善学生心肺功能 ,增强体质和促进身心健康的目的     

Approximation hardness of edge dominating set problems

We provide the first interesting explicit lower bounds on efficient approximability for two closely related optimization problems in graphs, MINIMUM EDGE DOMINATING SET and MINIMUM MAXIMAL MATCHING. We show that it is NP-hard to approximate the solution of both problems to within any constant factor smaller than . The result extends with negligible loss to bounded degree graphs and to everywhere dense graphs. An extended abstract of this paper was accepted at the 14th Annual International Symposium on Algorithms and Computation, ISAAC 2003.