Testing lack of fit of regression models under heteroscedasticity

A test is proposed for assessing the lack of fit of heteroscedastic nonlinear regression models that is based on comparison of nonparametric kernel and parametric fits. A data-driven method is proposed for bandwidth selection using the asymptotically optimal bandwidth of the parametric null model which leads to a test that has a limiting normal distribution under the null hypothesis and is consistent against any fixed alternative. The resulting test is applied to the problem of testing the lack of fit of a generalized linear model.     

初等树变换的算法改造

本文利用王氏代数对用初等树变换生成树的方法进行了改造,提出了一种新的初等树变换的算法。新算法较之原法简洁、直观、运算方便、概念清楚,并保留了原法的所有优点。     

单李代数不可约表示的标记

对于n秩单李代数g,当采用Dynkin关于素根的分类时,其不可约表示可以用n个非负整数Λ_(αi)标记,也可通过初等表示的权用数组li来标记。利用Cartan逆矩阵,我们给出了计算Λ_(α_i)与li之间关系的方法。对于B_n、C_n、D_n和F_4,利用Cartan逆矩阵证明了这些li是与采用Cartan关于素根的分类时的Λi是一致的。     

悬汞电极阴极溶出伏安法测定人发中的痕量硒

本工作用悬汞电极—示波极谱仪研究了Se(Ⅳ)在HClO_4—KI—EDTA底液中的阴极溶出测定的。在选定条件下,Se(Ⅳ)于—0.5V左右产生一灵敏的导数波,灵敏度为5×10~(-10)M(0.04ppb)。Se(Ⅳ)件浓度在1×10~(-7)M～5×10~(-9)M间与峰电流呈良好线性关系。本法用于人发中痕量硒的测定,结果满意。     

用跳马步系列研究奇素数阶规则完美幻方的个数

本文先介绍跳马步系列的有关概念及性质,然后用跳马步系列研究奇素数阶规则完美幻 方的个数。     

地区税收负担与经济发展的均衡分析

 1994年新税制实施以来至2000年,我国税收总收入达到58914.1亿元,年均增长17.5%,绝对额每年递增1200亿元。无疑,税收的突破性进展壮大了国家财力和中央宏观控制能力,但由于地区经济差距和税制设计等方面的原因,税制改革以来,我国地区间税负差距拉大,西部较落后地区税负提高,东部发达地区税负降低,这在一定程度上又阻碍了区域经济的协调发展。     

基于SEM模型的流动人口迁移意愿研究

流动人口迁移意愿一直是流动人口研究的热点问题。首次将结构方程模型应用到流动人口迁移意愿影响因素的研究中,通过选取经济条件、生活环境、社会福利保障、迁移意愿4个潜在变量,采用问卷调查获取数据,构建流动人口迁移意愿SEM模型。结果表明:基于SEM的流动人口迁移意愿影响因素分析模型拟合效果较好,为流动人口服务管理相关政策的制定,提供了更加科学的依据。     

家庭式迁移女性农民工劳动供给行为研究

随着城市化的不断推进,家庭式迁移已经成为农民工流动的重要模式。家庭式迁移的女性农民工需要同时扮演雇佣劳动者和家务主要承担者的双重角色,这种迁移模式对女性的劳动供给行为会造成重大的影响。利用浙江省农民工的调查数据,试图考察家庭式迁移女性农民工劳动供给的影响因素。分析结果表明:工作经验、培训经历、本地生活时间、工资对女性农民工的劳动供给具有显著影响;家庭结构的影响不显著,但子女或老人随迁会显著降低女性的劳动参与率和工作时间;分位数回归结果表明,各因素对女性工作时间不同分位数上的影响具有明显变化。     

Using p values to design statistical process control charts

Conventional Phase II statistical process control (SPC) charts are designed using control limits; a chart gives a signal of process distributional shift when its charting statistic exceeds a properly chosen control limit. To do so, we only know whether a chart is out-of-control at a given time. It is therefore not informative enough about the likelihood of a potential distributional shift. In this paper, we suggest designing the SPC charts using p values. By this approach, at each time point of Phase II process monitoring, the p value of the observed charting statistic is computed, under the assumption that the process is in-control. If the p value is less than a pre-specified significance level, then a signal of distributional shift is delivered. This p value approach has several benefits, compared to the conventional design using control limits. First, after a signal of distributional shift is delivered, we could know how strong the signal is. Second, even when the p value at a given time point is larger than the significance level, it still provides us useful information about how stable the process performs at that time point. The second benefit is especially useful when we adopt a variable sampling scheme, by which the sampling time can be longer when we have more evidence that the process runs stably, supported by a larger p value. To demonstrate the p value approach, we consider univariate process monitoring by cumulative sum control charts in various cases.     

Design-based random permutation models with auxiliary information

We extend the random permutation model to obtain the best linear unbiased estimator of a finite population mean accounting for auxiliary variables under simple random sampling without replacement (SRS) or stratified SRS. The proposed method provides a systematic design-based justification for well-known results involving common estimators derived under minimal assumptions that do not require specification of a functional relationship between the response and the auxiliary variables.