铅蓄电池正极材料的X射线衍射分析

本文用X射线衍射法对铅蓄电池正极活性材料二氧化铅进行了结构分析。结果表明:正极的二氧化铅同时存在二种不同的晶体结构。正方晶系的β—PbO_2主要分布在电极表面,针方晶系的α—PbO_2则分布在电极内部。如果将块状电极碾磨测量,α—PbO_2与β—PbO_2的含量几乎是相等的。     

中国摩托车行业’98分析报告

中国摩托车行业自５０年代初开始迈步,经过２０年（６０、７０年代）的摸索、１０年（１９８０—１９９０年）的进步、５年（１９９１—１９９５年）的快速发展,开始走向成熟。１９９６、１９９７年产量增幅放慢,分别比上年增长１８．５７％与７．９６％,较之“八五”...     

我国货币流通速度影响因素的格兰杰因果检验

货币流通速度一般是指单位货币在一年内平均使用次数,为了便于定量分析,定义货币流速Ｖ＝ＰＹＭ,（常称之为收入货币流速）,其中Ｐ是物价水平,Ｙ一般指实际国内生产总值（ＰＹ是名义国内生产总值即ＧＤＰ）,Ｍ是货币供应量。本文令Ｖ１和Ｖ２分别对应于狭义货币Ｍ１...     

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。     

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。     

西部大开发需要准确的统计数据—兼论地方政府统计的定位

文章结合贵州省实际和真实的统计现象,揭示出统计数据失真的堪忧局面及其成因.在此基础上,作者提出了提高统计数据质量,调整政府统计位置,适应西部大开发的六点建议.     

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.     

An Empirical Study of Statistical Properties of Variance Partition Coefficients for Multi-Level Logistic Regression Models

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003 Goldstein , H. ( 2003 ). Multilevel Statistical Models. 3rd ed . London : Edward Arnold . [Google Scholar]) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.