伸展构造背景下倾角资料的构造解释

系统总结了在伸展构造背景下，导致反映构造特征的地层倾角模式复杂化的多种因素。沉积相的不同、岩性变化、井眼状况和测井作业时间等多种因素都可能使地层倾角资料复杂化。进一步指出在拉张盆地中，进行倾角资料的构造解释，必须了解其构造样式的多样性和复杂性，解释存在的多解性。重点解剖了铲式断层在横剖面情况下，对于不同构造位置下的倾角模式。详细分析了一个倾角模式对应多种构造样式的倾角构造解释实例。倾角资料的构造解释应是综合解释，既要综合井筒的相关地质资料，又要综合测井与地质知识，还必须考虑综合地震资料。     

CAJ—CD规范存在的问题及对策

《中国学术期刊(光盘版)检索与评价数据规范》在参考文献著录方面存在着主要责任者缺位、文献分类含混、页码著录宽纵、转引缺项等问题。译作者和注疏校勘者同样应被视为主要责任者;文献分类方面,文献类型的界定应作出更详细的说明;页码著录,建议将文集、论文集、全集、选集、学位论文、报告几种参考文献的页码作为必选项;转引问题,建议分情况对待。     

On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models

While much used in practice, latent variable models raise challenging estimation problems due to the intractability of their likelihood. Monte Carlo maximum likelihood (MCML), as proposed by Geyer & Thompson (1992 ), is a simulation-based approach to maximum likelihood approximation applicable to general latent variable models. MCML can be described as an importance sampling method in which the likelihood ratio is approximated by Monte Carlo averages of importance ratios simulated from the complete data model corresponding to an arbitrary value of the unknown parameter. This paper studies the asymptotic (in the number of observations) performance of the MCML method in the case of latent variable models with independent observations. This is in contrast with previous works on the same topic which only considered conditional convergence to the maximum likelihood estimator, for a fixed set of observations. A first important result is that when is fixed, the MCML method can only be consistent if the number of simulations grows exponentially fast with the number of observations. If on the other hand, is obtained from a consistent sequence of estimates of the unknown parameter, then the requirements on the number of simulations are shown to be much weaker.     

Estimation of generalized linear latent variable models

Summary.  Generalized linear latent variable models (GLLVMs), as defined by Bartholomew and Knott, enable modelling of relationships between manifest and latent variables. They extend structural equation modelling techniques, which are powerful tools in the social sciences. However, because of the complexity of the log-likelihood function of a GLLVM, an approximation such as numerical integration must be used for inference. This can limit drastically the number of variables in the model and can lead to biased estimators. We propose a new estimator for the parameters of a GLLVM, based on a Laplace approximation to the likelihood function and which can be computed even for models with a large number of variables. The new estimator can be viewed as an M -estimator, leading to readily available asymptotic properties and correct inference. A simulation study shows its excellent finite sample properties, in particular when compared with a well-established approach such as LISREL. A real data example on the measurement of wealth for the computation of multidimensional inequality is analysed to highlight the importance of the methodology.     

Simple detection of outlying short time series

Sets of relatively short time series arise in many situations. One aspect of their analysis may be the detection of outlying series. We examine the performance of standard normal outlier tests applied to the means, or to simple functions of the means, of AR(1) series, not necessarily of equal lengths. Although unequal lengths of series implies that the means have unequal variances, that are only known approximately, it is shown that nominal significance levels hold good under most circumstances. Thus a standard outlier test can usefully be applied, avoiding the complication of estimating the time series' parameters. The test's power is affected by unequal lengths, being higher when the slippage occurs in one of the longer series     

Examples of the use of an equivalence theorem in constructing optimum experimental designs for random-effects nonlinear regression models

The problem considered is that of finding an optimum measurement schedule to estimate population parameters in a nonlinear model when the patient effects are random. The paper presents examples of the use of sensitivity functions, derived from the General Equivalence Theorem for D-optimality, in the construction of optimum population designs for such schedules. With independent observations, the theorem applies to the potential inclusion of a single observation. However, in population designs the observations are correlated and the theorem applies to the inclusion of an additional measurement schedule. In one example, three groups of patients of differing size are subject to distinct schedules. Numerical, as opposed to analytical, calculation of the sensitivity function is advocated. The required covariances of the observations are found by simulation.     

侵权诉讼的膨胀及对策

侵权纠纷是民事诉讼机制解决的主要对象。随着社会的发展,侵权案件逐渐增多,过量的侵权诉讼会带来很多不良后果,不仅是对法律制度本身的损害,更对经济发展产生严重的负面影响。要解决侵权诉讼的膨胀问题,必须找到控制侵权诉讼的正确途径。     

独立董事制度刍议

本文阐述了建立独立董事制度的重要意义,分析了我国上市公司独立董事制度存在的问题,并提出了健全我国独立董事制度的对策。     

简论潜在课程对提高大学生素质和创新能力的作用

素质教育是培养创新人才、构建和谐社会的重要教育实践环节,而潜在课程建设对素质教育具有不可替代的指导和促进作用。潜在课程指在学校自然环境、人文环境等因素影响下所构成的一种无形的、非正规的具有陶冶作用的集合体,具有潜在性、丰富性、持久性、经验性等特点,对大学生思想品德、实践能力等各方面的素质提高以及创新能力培养具有重要作用。高校潜在课程的开发和建设,为提高大学生综合素质,培养大学生创新能力提供了新的思路。     

串联稳压器基准误差放大电路的设计

针对串联型稳压器,设计了一种应用于串联型稳压器具有自建基准的新型误差放大电路。该电路具有构思巧妙,结构优化,易于集成及较高的开环增益,共模抑制比及交流特性的优点。通过验证,实测数据与仿真结果基本一致。