我国农村人口出生性别比偏高的动力机制研究

B超的滥用、强烈的男孩偏好以及对非法流产行为监控的失效共同构成我国出生性别比偏高的充要条件,三者中任一条件不满足都不可能出现出生性别比偏高。尽管B超发明和滥用前出生性别比并没有异常,但也不能说出生性别比偏高与受教育水平、传统文化等因素无关。事实上,这些因素通过影响男孩偏好和B超的可获得性而影响出生性别比。由此出发,促进出生性别比回复正常,短期内应标本兼治,以治标为主———坚决禁止B超的滥用,关键是加强立法和管理;长期内则必须治本———消除男孩偏好,关键是加速农村城市化。     

吕祖谦朱熹共讲月泉说质疑

明末以来的不少文献资料如《嘉靖浦江志略》、《乾隆浦江县志》都记载,吕祖谦、朱熹曾一同讲学于浙江浦江县的月泉书院,即第一次在宋孝宗乾道年间,第二次在孝宗淳熙八年.但如果就古代文献所提供的这两个时间来考察,则所谓吕祖谦、朱熹一起讲学月泉的事实属子虚乌有,属以讹传讹,不能信以为真.而之所以会产生这种误传,与此两人一个作为儒学正宗,一个被公认为浙东学派的实际开创者不无关系.这一事实也反映出一些旧地方志乘不一定值得信赖.     

幽独自得的硕人——再释《诗经·卫风·考》

《诗经·卫风·考》是隐士抒怀明志之作。诗篇具体生动而全面地描绘了隐士的生活情趣,突现其幽独之乐、拔俗之标、坚隐之节,表现出旷达闲适、和乐静穆的情调,给人留下深刻印象,具有感人的艺术魅力,对后世隐逸文学作品具有深远的影响。     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.     

A Population Approach to Analysis of Variance Models

Several authors have contributed to what can now be considered a rather complete theory for analysis of variance in cases with orthogonal factors. By using this theory on an assumed basic reference population, the orthogonality concept gives a natural definition of independence between factors in the population. By looking upon the treated units in designed experiments as a formal sample from a future population about which we want to make inference, a natural parametrization of expectations and variances connected to such experiments arises. This approach seems to throw light upon several controversial questions in the theory of mixed models. Also, it gives a framework for discussing the choice of conditioning in models     

A Multivariate Model for Repeated Failure Time Measurements

A parametric multivariate failure time distribution is derived from a frailty-type model with a particular frailty distribution. It covers as special cases certain distributions which have been used for multivariate survival data in recent years. Some properties of the distribution are derived: its marginal and conditional distributions lie within the parametric family, and association between the component variates can be positive or, to a limited extent, negative. The simple closed form of the survivor function is useful for right-censored data, as occur commonly in survival analysis, and for calculating uniform residuals. Also featured is the distribution of ratios of paired failure times. The model is applied to data from the literature     

同种商品不同月份期货组合风险评价模型研究及应用

以期货合约的每一交易日的对数涨跌率来反映市场风险,借助VaR风险价值法,运用加权核估计技术(WKDE)和指数加权滑动模型(EWMA),建立了基于期货组合中持有头寸不同且可以进行风险对冲的期货组合市场风险非线性叠加评价模型,解决了同种商品、不同月份期货组合每一交易日最大损失的确定问题,并通过实证研究验证了模型的实用性.该模型的特点一是借助WKDE法预测组合中单个合约每一交易日涨跌率最大日亏损值,充分体现了期货合约涨跌率的实际走势,使VaR估计更加精确.二是通过动态迁移相关系数矩阵的计算保证了模型的精确性.采用EWMA模型预测动态变化的方差-协方差矩阵,从实证的角度得到更精准的动态迁移相关系数矩阵.三是考虑了组合中多头和空头不同头寸之间的风险对冲,避免了实际中期货组合风险的线性相加而造成放大风险或减少风险的不准确性,从而能较好地保证了模型的预测精度及准确性.四是通过基于风险非线性叠加建立的期货组合风险评价模型解决了SPAN系统中期货组合风险的线性叠加问题,从而得到更合理的组合风险预测值.     

测试实数编码遗传算法的困难度

分析了遗传算法困难度测试在遗传算法研究中的重要意义. 鉴于当前这方面的研究集 中于二进制编码遗传算法,对实数编码遗传算法的困难度测试进行了分析. 探讨了实数编码遗 传算法困难度分析的适应值与距离相关系数测试法与基于随机游走模型的相关函数测试法, 提出了最佳一阶函数逼近测试法,做了大量实验,并根据实证分析结果对三种方法进行了比较 与评价.     

Limit theorems for dependent Bernoulli variables with statistical inference

We consider a class of dependent Bernoulli variables where the conditional success probability is a linear combination of the last few trials and the original success probability. We obtain its limit theorems including the strong law of large numbers, weak invariance principle, and law of the iterated logarithm. We also derive some statistical inference results which make the model applicable. Simulation results are exhibited as well to show that with small sample size the convergence rate is satisfying and the proposed estimators behave well.     

Nonparametric analysis of treatment effects with missing observations

This paper develops a test for comparing treatment effects when observations are missing at random for repeated measures data on independent subjects. It is assumed that missingness at any occasion follows a Bernoulli distribution. It is shown that the distribution of the vector of linear rank statistics depends on the unknown parameters of the probability law that governs missingness, which is absent in the existing conditional methods employing rank statistics. This dependence is through the variance–covariance matrix of the vector of linear ranks. The test statistic is a quadratic form in the linear rank statistics when the variance–covariance matrix is estimated. The limiting distribution of the test statistic is derived under the null hypothesis. Several methods of estimating the unknown components of the variance–covariance matrix are considered. The estimate that produces stable empirical Type I error rate while maintaining the highest power among the competing tests is recommended for implementation in practice. Simulation studies are also presented to show the advantage of the proposed test over other rank-based tests that do not account for the randomness in the missing data pattern. Our method is shown to have the highest power while also maintaining near-nominal Type I error rates. Our results clearly illustrate that even for an ignorable missingness mechanism, the randomness in the pattern of missingness cannot be ignored. A real data example is presented to highlight the effectiveness of the proposed method.