负二项环境因子的Fiducial限与Bayes限

本文给出成败型环境因子的定义,推导了负二项环境因子的Fiducial与Bayes精确限。为满足工程应用需要,给出了计算简便而又有较高精度的近似限,并举例说明。     

离散时间二型模糊双线性时滞系统的可达集估计与耗散性

文章研究了一类带有时变时滞和外部干扰的非线性系统的可达集估计与耗散控制问题.首先,考虑非线性系统的不确定参数,将非线性系统建模为区间二型模糊双线性时滞系统.其次,通过构造Lyapunov-Krasovskii泛函,提出区间二型模糊状态反馈控制准则,并利用反互凸组合引理界定二、三重时滞差分交叉项,得到保守性较小的区间二型模糊双线性闭环系统的可达集估计条件及系统严格耗散稳定性充分性条件.定理的条件可以保证系统的所有状态都收敛在一个椭圆内,并通过序列线性规划矩阵方法得到模糊控制器.最后,给出数值算例和仿真结果验证所得结论的有效性和正确性.     

指数和Weibull串联系统环境因子的统计推断

给出了Weibull串联系统环境因子的定义,且研究了元件寿命服从指数分布和Weibull分布时串联系统环境因子的点估计和区间估计,并利用模拟方法研究了所给点估计的精度和广义置信区间的覆盖率.模拟结果表明所给方法是令人满意的.     

离散型广义非线性纵向数据模型中偏离名义离差的检验及其功效模拟

离散型广义非线性模型包括Poisson,二项,负二项模型.本文讨论离散型广义非线性纵向数据模型中偏离名义离差的检验问题,得到了检验的score统计量,并利用MonteCarlo方法研究了检验统计量的性质.最后,利用杀虫剂数据说明了检验方法的应用.     

离散区间二型模糊双线性时滞系统的稳定控制

本文研究了带有常时滞的离散时间二型模糊双线性系统的状态反馈控制问题.首先,考虑隶属函数的不确定性,将非线性系统建模为区间二型模糊双线性系统.其次,基于Lyapunov稳定性理论,提出了区间二型模糊状态反馈控制准则,以保证区间二型模糊双线性闭环系统的稳定性.控制器的设计可以通过序列线性规划矩阵方法求解得到.最后,通过数值...     

分母为奇平方因子的二项式系数级数

根据一个已知级数,利用正弦积分与Clausen函数的结果,使用积分-裂项方法得到分母为1个平方因子,平方因子与1个,2个,3个一次因子乘积的二项系数级数.所给出二项式系数级数的和式是函数形式.并给出分母含有奇平方因子的二项式系数数值级数恒等式.     

基于状态分解的离散奇异时滞系统的容许性和H∞性能分析

针对一类具有外部扰动的离散奇异时滞系统,文章通过建立系统的微分-代数方程,研究其容许性及H_∞性能分析问题.为此,首先利用状态分解方法构造一个在二次型和二重积分二次型中都只含有部分状态量以及相关项的Lyapunov函数.其次,利用求和不等式,自由权矩阵方法等技术对函数的前向差分进行估计,建立一个使系统满足一定H_∞性能水平的容许性分析条件.该条件既能实现降低保守性的目的,又能尽可能地减少计算量.最后,通过数值实例验证所提方法的有效性和优越性.     

离散型随机变量高阶原点矩的一种新的递推计算方法

针对服从二项、泊松、几何、负二项、超几何、负超几何以及对数级数分布等离散型随机变量,给出了求其高阶原点矩的一个较为简单的递推计算方法.不仅非常容易地求出这些离散型随机变量的高阶原点矩,避免了计算阶乘矩或求导等复杂的运算,而且便于学生理解.论文还给出了这些离散型随机变量的3阶和4阶原点矩的表达式.     

加权的最小二乘形式矩阵Padé-型逼近

当最小二乘形式矩阵Pade-型逼近(LSMPTA)中Hankel矩阵呈病态时,其逼近解往往很不稳定.通过引入适当的权因子矩阵,将LSMPTA转化为与之等价且稳定性较高的一种新的LSMPTA,即加权的最小二乘形式矩阵Pade-型逼近,并给出了最佳权因子的选择标准.最后,通过数值实例说明了该方法的有效性.     

一个新的有两对共轭指数并在全平面积分的Hilbert型不等式

引入二对共轭指数,应用权函数的方法,给出一个新的有最佳常数因子并在全平面积分的Hilbert型不等式,同时考虑了对应的等价式.     

变环境情形下Weibull分布分组数据的参数估计

本文研究了变环境情形下Weibull分布分组数据可靠性估计的参数估计问题。给出一种基于EM算法的变环境分组数据Weibull分布参数估计方法,所得估计量具有良好的收敛性,模拟结果表明方法的实践可用性。     

Primal-Dual Path-Following Methods and the Trust-Region Updating Strategy for Linear Programming with Noisy Data

In this article, we consider the primal-dual path-following method and the trust-region updating strategy for the standard linear programming problem. For the rank-deficient problem with the small noisy data, we also give the preprocessing method based on the QR decomposition with column pivoting. Then, we prove the global convergence of the new method when the initial point is strictly primal-dual feasible. Finally, for some rank-deficient problems with or without the small noisy data from the NETLIB collection, we compare it with other two popular interior-point methods, i.e. the subroutine pathfollow.m and the built-in subroutine linprog.m of the MATLAB environment. Numerical results show that the new method is more robust than the other two methods for the rank-deficient problem with the small noise data.     

基于UGC大数据挖掘的大群体两阶段风险性应急决策方法

针对在重大突发事件应急决策大数据环境下决策者偏好的不确定性及偏离群体一致性导致的风险,提出一种基于UGC大数据挖掘的大群体两阶段风险性应急决策方法。首先,通过数据挖掘和自然语言处理方法从UGC中获取公众对事件的偏好信息并构建应急决策属性体系,利用TF-IDF方法结合专家评估信息确定属性权重;其次,建立一个意见开放式的两阶段决策流程,提出依据决策者意见的可靠度和准确度量化决策风险,利用聚类方法得到相应的成员权重,并使用TOPSIS法对决策方案进行排序。最后通过天津港“8·12”重大爆炸事故的案例分析和对比验证了所提出方法的可行性和有效性。     

残差EWMA-图对平稳自回归过程数据的检验能力

本文将SPC(Statistical Process Control)技术应用于自相关数据,使用的基本方法是对数据做残差处理,本文定义了一个衡量检验能力的指标。并给出了对于平稳自回归过程数据,在检验过程均值变化方面,残差EWMA—图检验能力强弱的条件。     

数据预处理对替代数据检验方法的影响

替代数据检验法是检验时间序列中是否存在确定性非线性成分的重要统计方法.通过研究差分和数据平滑运算对替代数据检验方法的影响,指出常用的线性滤波等数据预处理步骤破坏了序列的静态性质,从而会导致对零假设的错误拒绝.因此,建议应该直接利用原始时间序列而非应用了差分等非静态滤波运算后的时间序列生成替代数据,再进行假设检验,以免造成对零假设的错误拒绝.     

残差X—图对平稳可逆ARMA过程数据的检验能力

本文将SPC（Statistical Process Control）技术应用于自相关数据,使用的基本方法是对数据做残差处理,本文给出了对于平稳可逆的ARMA过程数据,在检验过程均值变化方面,残差X－图优于X－图的条件。     

Graphical Diagnostics for Markov Models for Categorical Data

Markov models are widely used as a method for describing categorical data that exhibit stationary and nonstationary autocorrelation. However, diagnostic methods are a largely overlooked topic for Markov models. We introduce two types of residuals for this purpose: one for assessing the length of runs between state changes, and the other for assessing the frequency with which the process moves from any given state to the other states. Methods for calculating the sampling distribution of both types of residuals are presented, enabling objective interpretation through graphical summaries. The graphical summaries are formed using a modification of the probability integral transformation that is applicable for discrete data. Residuals from simulated datasets are presented to demonstrate when the model is, and is not, adequate for the data. The two types of residuals are used to highlight inadequacies of a model posed for real data on seabed fauna from the marine environment.

Supplemental materials, including an R-package RMC with functions to perform the diagnostic measures on the class of models considered in this article, are at the journal’s website. The R-package is also available at CRAN.     

油价波动和资源环境补偿视角下石油资源税率研究——基于山东省数据

油价、资源与环境统筹管理政策缺失导致石油资源外部性问题日益严重,从油价波动和资源环境补偿视角出发研究石油资源税率是解决石油资源外部性,实现对油价、资源与环境统筹管理的关键。基于山东省2000~2013年石油资源开采行业数据,根据使用者成本法测算山东省石油开采行业的资源耗减成本,发现当前资源税费比率应提高14%;根据生态补偿标准模型测算生态环境成本,结合大量实地调研,指出生态环境补偿水平应从目前补偿水平的22%逐步提高至完全补偿生态环境成本。然后,根据价值对等原则构建资源生态环境补偿方程,探索性地计算了基于油价波动的石油资源税率,发现当油价处于(23~52)、(52~78)、(78~115)美元/桶的油价区间时,在7%折现率下分别对应17.51%、18.84%、19.04%的补偿税率,得出结论:当前条件下将资源税费与环境补偿费用合并征收,需要将补偿税率逐步提高至15%~20%。最后,从税率确定、计征方式以及监管体系三方面提出了执行对策。     

Guiding Data Analysts with Visual Statistical Strategies

Abstract

The concept of statistical strategy is introduced and used to develop a structured graphical user interface for guiding data analysis. The interface visually represents statistical strategies that are designed by expert data analysts to guide novices. The representation is an abstraction of the expert's concepts of the essence of a data analysis. We argue that an environment that visually guides and structures data analysis will improve data analysis productivity, accuracy, accessibility, and satisfaction in comparison to an environment without such aids, especially for novice data analysts. Our concepts are based on notions from cognitive science, and can be empirically evaluated. The interface consists of two interacting windows—the guidemap and the workmap. Each window contains a graph that has nodes and edges. The guidemap graph represents the statistical strategy for a specific statistical task (such as describing data). Nodes represent potential data analysis actions that can be taken by the system. Edges represent potential actions that can be taken by the analyst. The guidemap graph exists prior to the data analysis session, having been created by an expert. The workmap graph represents the complete history of all steps taken by the data analyst. It is constructed during the data analysis session as a result of the analyst's actions. Workmap nodes represent data sets, data models, or data analysis procedures that have been created or used by the analyst. Workmap edges represent the chronological sequence of the analyst's actions. One workmap node is highlighted to indicate which statistical object is the focus of the strategy. We illustrate our concepts with ViSta, the Visual Statistics system that we have developed.     

Heuristic Methods for the Data Placement Problem

Databases require a management system which is capable of retrieving and storing information as efficiently as possible. The data placement problem is concerned with obtaining an optimal assignment of data tuples onto secondary storage devices. Such tuples have complicated interrelationships which make it difficult to find an exact solution to our problem in a realistic time.We therefore consider heuristic methods—three of which are discussed and compared — the ‘greedy’ graph-collapsing method, the probabilistic hill-climbing method of simulated annealing and a third ‘greedy’ heuristic, the random improvement method, which is a local search heuristic. Overall, the best performance is obtained from the graph-collapsing method for the less complicated situations, but for larger-scale problems with complex interrelationships between tuples the simulated annealing and random improvement algorithms give better results.