辽河流域辽宁区域水资源承载力分析

在分析辽河流域辽宁区域水资源现状及存在问题的基础上,建立考虑水资源、社会、经济以及生态环境系统的水资源承载力评价指标体系,应用模糊集对分析法对辽河流域辽宁区域各行政区现状年2005年、规划水平年2020年和2030年进行评价。结果表明,辽河流域辽宁区域除抚顺、铁岭、丹东、锦州、营口承载力水平为Ⅱ级外,其他地区均为Ⅲ级,水资源已接近饱和值,开发利用潜力较小。在此基础上,提出依靠跨流域调水、节水、雨水污水资源化等措施,提高辽河流域辽宁区域水资源承载力。     

Fast bandwidth selection for estimation of the pair correlation function

ABSTRACT

Kernel estimation is a popular approach to estimation of the pair correlation function which is a fundamental spatial point process characteristic. Least squares cross validation was suggested by Guan [A least-squares cross-validation bandwidth selection approach in pair correlation function estimations. Statist Probab Lett. 2007;77(18):1722–1729] as a data-driven approach to select the kernel bandwidth. The method can, however, be computationally demanding for large point pattern data sets. We suggest a modified least squares cross validation approach that is asymptotically equivalent to the one proposed by Guan but is computationally much faster.     

Globally intensity-reweighted estimators for K- and pair correlation functions

We introduce new estimators of the inhomogeneous K-function and the pair correlation function of a spatial point process as well as the cross K-function and the cross pair correlation function of a bivariate spatial point process under the assumption of second-order intensity-reweighted stationarity. These estimators rely on a ‘global’ normalisation factor which depends on an aggregation of the intensity function, while the existing estimators depend ‘locally’ on the intensity function at the individual observed points. The advantages of our new global estimators over the existing local estimators are demonstrated by theoretical considerations and a simulation study.     

Structured Spatio-Temporal Shot-Noise Cox Point Process Models, with a View to Modelling Forest Fires

Abstract.  Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable for statistical analysis, using spatio-temporal versions of intensity and inhomogeneous K -functions, quick estimation procedures based on composite likelihoods and minimum contrast estimation, and easy simulation techniques. These advantages are demonstrated in connection with the analysis of a relatively large data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent.     

Job Durations With Worker- and Firm-Specific Effects: MCMC Estimation With Longitudinal Employer–Employee Data

We study job durations using a multivariate hazard model allowing for worker-specific and firm-specific unobserved determinants. The latter are captured by unobserved heterogeneity terms or random effects, one at the firm level and another at the worker level. This enables us to decompose the variation in job durations into the relative contribution of the worker and the firm. We also allow the unobserved terms to be correlated in a model that is primarily relevant for markets with small firms. For the empirical analysis, we use a Portuguese longitudinal matched employer–employee dataset. The model is estimated with a Bayesian Markov chain Monte Carlo (MCMC) estimation method. The results imply that unobserved firm characteristics explain almost 40% of the systematic variation in log job durations. In addition, we find a positive correlation between unobserved worker and firm characteristics.     

Geometrically Corrected Second Order Analysis of Events on a Linear Network,with Applications to Ecology and Criminology

Abstract. We study point patterns of events that occur on a network of lines, such as road accidents recorded on a road network. Okabe and Yamada developed a ‘network K function’, analogous to Ripley's K function, for analysis of such data. However, values of the network K‐function depend on the network geometry, making interpretation difficult. In this study we propose a correction of the network K‐function that intrinsically compensates for the network geometry. This geometrical correction restores many natural and desirable properties of K, including its direct relationship to the pair correlation function. For a completely random point pattern, on any network, the corrected network K‐function is the identity. The corrected estimator is intrinsically corrected for edge effects and has approximately constant variance. We obtain exact and asymptotic expressions for the bias and variance of under complete randomness. We extend these results to an ‘inhomogeneous’ network K‐function which compensates for a spatially varying intensity of points. We demonstrate applications to ecology (webs of the urban wall spider Oecobius navus) and criminology (street crime in Chicago).     

Ka频段微带四次谐波混频器

介绍了一种Ka频段的微带四次谐波混频器的混频原理和设计方法。该混频器主要由波导-微带过渡,输入、输出滤波器以及匹配网络和反向并联混频二极管对组成。根据计算机辅助设计软件的仿真结果,在介电常数为2.22,厚度为0.254 mm的RF-Duroid 5880介质基片上制作了电路。当射频频率为34.2~35.2 GHz,本振频率为8.525~8.775 GHz,中频频率为100 MHz时,测得的变频损耗小于10.5 dB,其中最佳值为8.5 dB。     

对历史名校的师资培养方法探讨

高素质、高质量教师队伍的建设,可为学生的学习提供专业的教师队伍,所以,为加快各校师资力量的培养,可参考历史名校师资培养的策略,找到培养优秀教师的渠道,从而提高青年教师的教学水平,丰富其经验,为学生提供高质量的教学服务。     

Optimal allocation of subjects in a matched pair cluster-randomized trial with fixed number of heterogeneous clusters

In cluster-randomized trials, investigators randomize clusters of individuals such as households, medical practices, schools or classrooms despite the unit of interest are the individuals. It results in the loss of efficiency in terms of the estimation of the unknown parameters as well as the power of the test for testing the treatment effects. To recoup this efficiency loss, some studies pair similar clusters and randomize treatment within pairs. However, the clusters within a treatment arm might be heterogeneous in nature. In this article, we propose a locally optimal design that accounts the clusters heterogeneity and optimally allocates the subjects within each cluster. To address the dependency of design on the unknown parameters, we also discuss Bayesian optimal designs. Performances of proposed designs are investigated numerically through some data examples.     

Confidence intervals for the difference of marginal probabilities in clustered matched-pair binary data

Although there are several available test statistics to assess the difference of marginal probabilities in clustered matched‐pair binary data, associated confidence intervals (CIs) are not readily available. Herein, the construction of corresponding CIs is proposed, and the performance of each CI is investigated. The results from Monte Carlo simulation study indicate that the proposed CIs perform well in maintaining the nominal coverage probability: for small to medium numbers of clusters, the intracluster correlation coefficient‐adjusted McNemar statistic and its associated Wald or Score CIs are preferred; however, this statistic becomes conservative when the number of clusters is larger so that alternative statistics and their associated CIs are preferred. In practice, a combination of the intracluster correlation coefficient‐adjusted McNemar statistic with an alternative statistic is recommended. To illustrate the practical application, a real clustered matched‐pair collection of data is used to illustrate testing the difference of marginal probabilities and constructing the associated CIs. Copyright © 2012 John Wiley & Sons, Ltd.