模拟混相驱动态的拟四组分模型

通常模拟混相驱动态采用组分模型,由于组分模型求解工作量大,计算速度慢,要求输入的参数较多,而这些参数很难取全取准,同时组分模型不易被油藏工程师所掌握。因此,介绍了一种模拟混相驱动态的模拟模型,该模型是在黑油模型基础上发展起来的拟四组分模型,它兼有黑油模型和多组分模型的某些优点,如黑油模型的稳定性好和计算速度快、组分模型的可模拟凝析气藏和混相驱等;给出了数学模型及各种物理参数以及混相流体性质的处理方法。该模型还以SPE为例进行计算,结果与SPE的结果一致,从而验证了本模型的可靠性。     

Hypothesis Tests for Neyman's Bias in Case–Control Studies

Survival bias is a long recognized problem in case–control studies, and many varieties of bias can come under this umbrella term. We focus on one of them, termed Neyman's bias or ‘prevalence–incidence bias’. It occurs in case–control studies when exposure affects both disease and disease-induced mortality, and we give a formula for the observed, biased odds ratio under such conditions. We compare our result with previous investigations into this phenomenon and consider models under which this bias may or may not be important. Finally, we propose three hypothesis tests to identify when Neyman's bias may be present in case–control studies. We apply these tests to three data sets, one of stroke mortality, another of brain tumors, and the last of atrial fibrillation, and find some evidence of Neyman's bias in the former two cases, but not the last case.     

Likelihood ratio order of parallel systems under multiple-outlier models

This paper studies the likelihood ratio ordering of parallel systems under multiple-outlier models. We introduce a partial order, the so-called θ-order, and show that the θ-order between the parameter vectors of the parallel systems implies the likelihood ratio order between the systems.     

Likelihood ratio tests for multivariate normality

This paper presents some powerful omnibus tests for multivariate normality based on the likelihood ratio and the characterizations of the multivariate normal distribution. The power of the proposed tests is studied against various alternatives via Monte Carlo simulations. Simulation studies show our tests compare well with other powerful tests including multivariate versions of the Shapiro–Wilk test and the Anderson–Darling test.     

Sum,product and ratio of Pareto and gamma variables

The exact distributions of X+Y, X Y and X/(X+Y) are studied when X and Y are independent Pareto and gamma random variables. Applications are discussed, to real problems in clinical trials, computer networks and economics.     

A comparative study of confidence intervals for negative binomial proportion

In this paper, we investigate four existing and three new confidence interval estimators for the negative binomial proportion (i.e., proportion under inverse/negative binomial sampling). An extensive and systematic comparative study among these confidence interval estimators through Monte Carlo simulations is presented. The performance of these confidence intervals are evaluated in terms of their coverage probabilities and expected interval widths. Our simulation studies suggest that the confidence interval estimator based on saddlepoint approximation is more appealing for large coverage levels (e.g., nominal level≤1% ) whereas the score confidence interval estimator is more desirable for those commonly used coverage levels (e.g., nominal level>1% ). We illustrate these confidence interval construction methods with a real data set from a maternal congenital heart disease study.     

Testing variance components in balanced linear growth curve models

It is well known that the testing of zero variance components is a non-standard problem since the null hypothesis is on the boundary of the parameter space. The usual asymptotic chi-square distribution of the likelihood ratio and score statistics under the null does not necessarily hold because of this null hypothesis. To circumvent this difficulty in balanced linear growth curve models, we introduce an appropriate test statistic and suggest a permutation procedure to approximate its finite-sample distribution. The proposed test alleviates the necessity of any distributional assumptions for the random effects and errors and can easily be applied for testing multiple variance components. Our simulation studies show that the proposed test has Type I error rate close to the nominal level. The power of the proposed test is also compared with the likelihood ratio test in the simulations. An application on data from an orthodontic study is presented and discussed.     

Two non parametric methods for change-point detection in distribution

The change-point detection problem is determining whether a change has taken place. Two non parametric methods based on empirical likelihood and the likelihood ratio are proposed for detecting a change-point problem in distributions for independent observations. Numerical studies are carried out to evaluate the performance of the proposed methods. The simulation results demonstrate that the proposed methods are robust, that is, they perform well regardless of whether the observations are from the same distribution family.     

对华北油田勘探历程的再认识

华北油田是我国最早发现古潜山海相碳酸盐岩油气藏的地方,也是产量骤起骤降幅度最大的一个油田,它的勘探过程中蕴含着太多丰富的经验值得总结.从任4井发现的细节入手进行回顾,对华北油田勘探经验中的古潜山、碳酸盐岩、震旦系灰岩等关键问题进行了深入思考.指出按有机成油论的学说很难将华北油田的历史经验深入总结下去,应按无机成油论的观点,对华北油田的历史经验进行再认识.     

欧洲债务危机的主要成因分析

肇始于希腊的欧洲债务危机到目前为止都没有停息的迹象,甚至还呈蔓延之势。欧洲债务危机爆发的直接原因是在金融危机的背景下,政府支出规模持续扩大,导致财政赤字居高不下,最终使得国债规模超过政府的偿还能力,出现明显的违约可能性。同时,国际竞争力不足,导致出口受阻,使得资金问题更加严重。从更深层次看,产业结构不合理,经济发展速度缓慢,过低的投资率和储蓄率及过高的储蓄投资转化率,都是导致欧债危机的重要原因。