The Multiscale Importance of Road Segments in a Network Disruption Scenario: A Risk‐Based Approach

This article addresses the problem of the multiscale importance of road networks, with the aim of helping to establish a more resilient network in the event of a road disruption scenario. A new model for identifying the most important roads is described and applied on a local and regional scale. The work presented here represents a step forward, since it focuses on the interaction between identifying the most important roads in a network that connect people and health services, the specificity of the natural hazards that threaten the normal functioning of the network, and an assessment of the consequences of three real‐world interruptions from a multiscale perspective. The case studies concern three different past events: road interruptions due to a flood, a forest fire, and a mass movement. On the basis of the results obtained, it is possible to establish the roads for which risk management should be a priority. The multiscale perspective shows that in a road interruption the regional system may have the capacity to reorganize itself, although the interruption may have consequences for local dynamics. Coordination between local and regional scales is therefore important. The model proposed here allows for the scaling of emergency response facilities and human and physical resources. It represents an innovative approach to defining priorities, not only in the prevention phase but also in terms of the response to natural disasters, such as awareness of the consequences of road disruption for the rescue services sent out to local communities.     

A Non‐Parametric Estimator of the Spectral Density of a Continuous‐Time Gaussian Process Observed at Random Times

Abstract. In numerous applications data are observed at random times and an estimated graph of the spectral density may be relevant for characterizing and explaining phenomena. By using a wavelet analysis, one derives a non‐parametric estimator of the spectral density of a Gaussian process with stationary increments (or a stationary Gaussian process) from the observation of one path at random discrete times. For every positive frequency, this estimator is proved to satisfy a central limit theorem with a convergence rate depending on the roughness of the process and the moment of random durations between successive observations. In the case of stationary Gaussian processes, one can compare this estimator with estimators based on the empirical periodogram. Both estimators reach the same optimal rate of convergence, but the estimator based on wavelet analysis converges for a different class of random times. Simulation examples and an application to biological data are also provided.     

多标度条件下资本市场波动的级串方向和结构

对上证综指多标度条件下波动级串方向和结构的实证研究发现,在4days临界标度范围内,大小波动间互为因果;超出临界标度,大小波动间表现出单方向性特征.运用交叉相关系数和功率谱方法从相关性和能量耗散2个角度对多标度波动级串传递方向的分析同样显示,在101～103min的3个数量级广泛标度范围内,大波动对于小波动具有较强预测能力,波动级串结构表现出大波动影响小波动变化的单方向特征.在此基础上,提出了4类"递进"的资本市场波动级串模型及其运用于风险管理的基本思路.     

双光子对撞过程的人工色理论尝试

考虑了多标度人工色 (multiscalewalkingtechnicolor,简称MWTC)模型中赝标哥尔斯通玻色子 (pseudo Goldstonebosons ,简称PGBs)对γγ→bb过程的Yukawa修正。发现在一定的参数范围内 ,PGBs对γγ→bb散射截面的修正超过 10 % ;而PGBs对过程e+ e-→γγ→bb的相对修正 ,在laserback scatteringphotons模式下最大可达 - 5 9% ,在beamstrahlungphotons模式下最大只有 - 2 2 % ;这些修正将为在下一代高能光子碰撞实验上寻找人工色理论的信息提供参考     

B介子稀有衰变对多标度人工色模型的限制

在多标度人工色模型下计算了荷电PG玻色子对B介子稀有衰变B→Xs,dνν和Bs,d→l+ l-的贡献 ,抽出了描写新物理贡献的Co(xi)函数。计算表明 :K .Lane等人提出的多标度人工色模型与B介子稀有衰变的实验数据相矛盾     

Multiscale change point detection for dependent data

In this article we study the theoretical properties of the simultaneous multiscale change point estimator (SMUCE) in piecewise-constant signal models with dependent error processes. Empirical studies suggest that in this case the change point estimate is inconsistent, but it is not known if alternatives suggested in the literature for correlated data are consistent. We propose a modification of SMUCE scaling the basic statistic by the long run variance of the error process, which is estimated by a difference-type variance estimator calculated from local means from different blocks. For this modification we prove model consistency for physical-dependent error processes and illustrate the finite sample performance by means of a simulation study.     

中国股票市场多标度幂律特征和临界现象

本文对上海证券交易所综合股价指数(SSECI)收益率多标度条件下的分布特征和临界现象的研究发现,收益率分布的中心部分服从Lévy分布,尾部近似对称分布,依幂律衰减,负尾的衰减略高于正尾,整体衰减远超出Lévy律0<α<2的范围,也高于成熟市场α≈3的水平。此外,上证综指收益率在多标度条件下还表现出临界现象,在标度△t>4days时渐进收敛于正态分布,成熟市场△t≈4days的临界值对中国市场具有普适性。     

多标度条件下的幂相关性：中国股市收益率的经验分析

对上海证券交易所综合股价指数(SSECI)收益率(5-min数据集)多标度条件下的相关性研究发现,在多重分形消除趋势波动法MF-DFA(适用于非稳定序列多点间相关性分析)的度量框架下,收益率序列G和G在101×5~105×5min的4个数量级标度条件下具有非唯一的幂相关指数,不同波动幅度表现出不同的长程相关性特征;收益率序列G的幂相关指数谱宽度大于序列|G|的指数谱宽度,平均谱指数小于|G|的平均谱指数,序列|G|表现出较G更强的正向持久性。     

供给与需求驱动型原油价格变动对股票市场的多时间尺度影响研究

不同时间尺度下，供给和需求驱动型原油价格变动对股票市场的影响具有差异性，本文结合小波变化及向量自回归模型，从影响方向、影响强度及影响持续时间三个角度对这种差异性展开研究。首先，在多时间尺度下识别供给和需求驱动型原油价格变动；随后，就不同类型原油价格变动对全球综合股指的动态影响进行分析。结果发现：1）两类原油价格变动对股票市场在短、中及长期下均有显著影响，但需求驱动型原油价格变动在超短期（尺度1：2-4个月）和超长期（尺度6：64-128个月）下对股票市场没有显著影响；2）两类原油价格变动对股票市场的影响方向在短期和中期下具有随机性，在长期下具有正向影响；3）两类原油价格变动对股票市场的影响强度在短期和中期较在长期要高出至少60%；4）两类原油价格变动对股票市场的影响时间随着时间尺度的增长而增长，由短期下的20个月左右延长至长期下的60个月以上。     

Likelihood and Non-parametric Bayesian MCMC Inference for Spatial Point Processes Based on Perfect Simulation and Path Sampling

We consider the combination of path sampling and perfect simulation in the context of both likelihood inference and non‐parametric Bayesian inference for pairwise interaction point processes. Several empirical results based on simulations and analysis of a data set are presented, and the merits of using perfect simulation are discussed.