On the Multivariate Upcrossings Index

The multivariate extremal index function is a measure of the clustering among the extreme values of a multivariate stationary sequence. In this article, we introduce a measure of the degree of clustering of upcrossings in a multivariate stationary sequence, called multivariate upcrossings index, which is a multivariate generalization of the concept of upcrossings index. We derive the main properties of this function, namely the relations with the multivariate extremal index and the clustering of upcrossings.

Imposing general local and asymptotic dependence restrictions on the sequence or on its marginals we compute the multivariate upcrossings index from the marginal upcrossings indices and from the joint distribution of a finite number of variables. A couple of illustrative examples are exploited.     

考虑复杂关联情境的城市典型生命线运行风险因素识别方法研究

城市典型生命线以供热、电力、燃气系统为代表,具有公共性强、风险性高、关联性显著的特点。研究城市典型生命线运行风险因素识别问题对于相关部门防范风险具有重要意义,但现实中由多系统、多风险因素以及各类关联形成的复杂关联情境增加了解决该问题的难度。为此,本文首先构建了具有层级网络结构的风险因素识别框架,然后提出了一种考虑复杂关联情境的风险因素识别方法,将各专家针对系统关联和风险因素关联给出的语言评价信息转化为二元语义,并将决策试验与评价实验室（DEMATEL）法和Two-Additive Choquet（TAC）积分算子扩展到二元语义环境,进而实现各类关联的综合集成,从而确定风险因素的排序和归类,便于决策者研判风险根源、明晰风险因素本质。最后,以北京某样区为例验证了所提方法的潜在应用价值,并根据识别结果制定了针对性的风险防范策略,能够为相关部门联调联动开展风险防范提供决策支持。     

Religious involvement and group identification: The case of Hispanics in the United States

This study examines the link between religious involvement and racial group identification among Hispanics in the United States. Relying on the multifaceted nature of religious involvement, this study focuses on five dimensions of religious involvement—church attendance, prayer, the importance one places on religion, one's belief in God's love, and religious affiliation. Using the data from the Panel Study of American Religion and Ethnicity (1st wave, 2006), this study employs regression analysis. The results show that, among the five dimensions of religious involvement, only church attendance has a significant effect on racial group identification; Hispanics who frequently attend church are more likely to identify with Hispanics. This study suggests that church attendance increases Hispanics’ group identification for two reasons: first, because of the formation of Hispanic-oriented churches; and second, because of the intense interaction among Hispanics within their church communities.     

Theoretical limits of component identification in a separable nonlinear least-squares problem

We provide theoretical insights into component identification in a separable nonlinear least-squares problem in which the model is a linear combination of nonlinear functions (called components in this paper). Within this research, we assume that the number of components is unknown. The objective of this paper is to understand the limits of component discovery under the assumed model. We focus on two aspects. One is sensitivity analysis referring to the ability of separating regression components from noise. The second is resolution analysis referring to the ability of de-mixing components that have similar location parameters. We use a wavelet transformation that allows to zoom in at different levels of details in the observed data. We further apply these theoretical insights to provide a road map on how to detect components in more realistic settings such as a two-dimensional nuclear magnetic resonance experiment for protein structure determination.     

Critical Scale for a Continuous AIMD Model

A scaled version of the general AIMD model of transmission control protocol (TCP) used in Internet traffic congestion management leads to a Markov process x(t) representing the time dependent data flow that moves forward with constant speed on the positive axis and jumps backward to γx(t), 0 < γ < 1 according to a Poisson clock whose rate α(x) depends on the interval swept in between jumps. We give sharp conditions for Harris recurrence and analyze the convergence to equilibrium on multiple scales (polynomial, fractional exponential, exponential) identifying the critical case xα(x) ～ β. Criticality has different behavior according to whether it occurs at the origin or infinity. In each case, we determine the transient (possibly explosive), null—and positive—recurrent regimes by comparing β to ( ? ln?γ)^{? 1}.     

Market Structure and Multiple Equilibria in Airline Markets

We provide a practical method to estimate the payoff functions of players in complete information, static, discrete games. With respect to the empirical literature on entry games originated by Bresnahan and Reiss (1990) and Berry (1992), the main novelty of our framework is to allow for general forms of heterogeneity across players without making equilibrium selection assumptions. We allow the effects that the entry of each individual airline has on the profits of its competitors, its “competitive effects,” to differ across airlines. The identified features of the model are sets of parameters (partial identification) such that the choice probabilities predicted by the econometric model are consistent with the empirical choice probabilities estimated from the data. We apply this methodology to investigate the empirical importance of firm heterogeneity as a determinant of market structure in the U.S. airline industry. We find evidence of heterogeneity across airlines in their profit functions. The competitive effects of large airlines (American, Delta, United) are different from those of low cost carriers and Southwest. Also, the competitive effect of an airline is increasing in its airport presence, which is an important measure of observable heterogeneity in the airline industry. Then we develop a policy experiment to estimate the effect of repealing the Wright Amendment on competition in markets out of the Dallas airports. We find that repealing the Wright Amendment would increase the number of markets served out of Dallas Love.     

Testing for Linear Regression Relationships in Randomly Right-Censored Varying-Coefficient Models

A test statistic is constructed to test linear relationships in randomly right-censored varying-coefficient models. A residual-based bootstrap procedure is employed to derive the p-value of the test. The performance of the test is examined by extensive simulations. The simulation results show that the bootstrap estimate of the null distribution of the test statistic is approximately valid and the test method with the residual-based bootstrap works satisfactorily for at least moderate censoring rates of the response. Furthermore, the proposed test is applied to the Stanford heart transplant data for exploring a linear regression relationship between the logrithm of the survival time and the age of the patients.     

Equivalence of parametric identifiability and estimability

Given that estimators are monotone functions of observations, parametric identiflability is shown to be both necessary and sufficient for estimability.