Residual analysis for spatial point processes (with discussion)

Summary.  We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q – Q -plots of the residuals are effective in diagnosing interpoint interaction.     

一类多元Gauss-Weierstrass算子线性组合的加权逼近

该文给出了一类多元Gauss-Weierstrass算子线性组合加Jacobi权在一致逼近下的正、逆定理和逼近阶的特征刻划     

Influence diagnostics and outlier tests for semiparametric mixed models

Summary. Semiparametric mixed models are useful in biometric and econometric applications, especially for longitudinal data. Maximum penalized likelihood estimators (MPLEs) have been shown to work well by Zhang and co-workers for both linear coefficients and nonparametric functions. This paper considers the role of influence diagnostics in the MPLE by extending the case deletion and subject deletion analysis of linear models to accommodate the inclusion of a nonparametric component. We focus on influence measures for the fixed effects and provide formulae that are analogous to those for simpler models and readily computable with the MPLE algorithm. We also establish an equivalence between the case or subject deletion model and a mean shift outlier model from which we derive tests for outliers. The influence diagnostics proposed are illustrated through a longitudinal hormone study on progesterone and a simulated example.     

广义孙子定理

给出了一次同余式组的解的计算公式.     

汉代诸子论吏治与治吏

官吏是封建国家各项政策的具体执行者。因为政策执行情况的好与坏 ,直接关系着皇朝的长治久安 ,所以治吏便成为治国的很重要的一方面。汉代诸子通过对两汉各个时期吏治状况的论述 ,深刻揭露了官官相护、贪污奢侈、对劳动人民的中间盘剥等吏治腐败现实。在此基础上 ,他们又纷纷提出相应的治吏主张 ,如打击贪污腐败、加强法律监督、增加官吏俸禄等     

多元线性回归方程及其应用

通过建立多元线性回归的数学模型,利用最小二乘估计得到正规方程组并进行相关性检验,从而解决相关实际问题。     

中国古代管理中的四环均衡发展思想

政治是经济的集中体现 ,直接影响着经济的发展和吏治、教育的建设 ;经济的发展首先要有吏治的保证和教育的支持 ;教育为政治经济服务 ,为整个社会输送干部和人才 ;吏治是在政治的正确指向下 ,通过教育的培养 ,完成对社会各方面的管理特别是经济的管理的。四环是互相套合的 ,是要均衡发展的。     

对偶线性规划问题性质探析

探讨对偶线性规划的原始问题与对偶问题的属性，阐述两者的区别和内在联系，用较简便的方法论证其重要性质，揭示可行解与目标函数、可行解与最优解的关系，指出线性规划问题最优解从约束条件较少的对偶问题寻求为另一较简便之方法。     

英文段落的推展模式及内部衔接机制初探

从篇章语言学的角度看 ,英文段落依层级的概括性推展 ,并呈典型的直线性发展模式。英文作者主要利用词汇相等链、链式结构和编列结构衔接段中各语句来推展段落 ,从而使段落具有交际功能。英文语篇结构模式对英文习得者来说具有实际指导意义     

ELICITING A DIRECTED ACYCLIC GRAPH FOR A MULTIVARIATE TIME SERIES OF VEHICLE COUNTS IN A TRAFFIC NETWORK

The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynamic linear models. The conditional independence and causal structure in the time series can be represented by a directed acyclic graph (DAG). The DAG not only gives a useful pictorial representation of the multivariate structure, but it is also used to build the LMDM. Therefore, eliciting a DAG which gives a realistic representation of the series is a crucial part of the modelling process. A DAG is elicited for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a DAG for the time series suitable for use with an LMDM.