小麦新品种“绵阳26”主要性状与产量的关系

对45个试验点的资料分析,多抗、丰产、优质、广适小麦新品种绵阳26的主要性状有效穗x1、穗粒数x2和千粒x3、单穗重x4与产量y的回归方程为：y＝－614．8425＋9.8683x1＋7.3223x2＋10．5315x3＋22．5748x4。经偏回归和偏相关分析,产量构成因素中,千粒重、有效穗对绵阳26产量的贡献和影响最大（b'3＝1．7435,b'1＝1．5372,R3y.＝0．7983,R1y＝0．6991）。在现有产量的基础上稳定千粒重,主攻穗数和穗粒数,是发挥绵阳26高产潜力的决定因素。     

常系数齐次线性微分方程组与其相应的差分方程组之间的联系

给出了求解常系数线性齐次微分方程组和常系数线性齐次差分方程组的一个方法,指出了这两种方程组之间存在的一个有趣关系．     

Spatial variation in risk of disease: a nonparametric binary regression approach

A common problem in environmental epidemiology is the estimation and mapping of spatial variation in disease risk. In this paper we analyse data from the Walsall District Health Authority, UK, concerning the spatial distributions of cancer cases compared with controls sampled from the population register. We formulate the risk estimation problem as a nonparametric binary regression problem and consider two different methods of estimation. The first uses a standard kernel method with a cross-validation criterion for choosing the associated bandwidth parameter. The second uses the framework of the generalized additive model (GAM) which has the advantage that it can allow for additional explanatory variables, but is computationally more demanding. For the Walsall data, we obtain similar results using either the kernel method with controls stratified by age and sex to match the age–sex distribution of the cases or the GAM method with random controls but incorporating age and sex as additional explanatory variables. For cancers of the lung or stomach, the analysis shows highly statistically significant spatial variation in risk. For the less common cancers of the pancreas, the spatial variation in risk is not statistically significant.     

Application of Markov chain Monte Carlo methods to modelling birth prevalence of Down syndrome

Data collected before the routine application of prenatal screening are of unique value in estimating the natural live-birth prevalence of Down syndrome. However, much of these data are from births from over 20 years ago and they are of uncertain quality. In particular, they are subject to varying degrees of underascertainment. Published approaches have used ad hoc corrections to deal with this problem or have been restricted to data sets in which ascertainment is assumed to be complete. In this paper we adopt a Bayesian approach to modelling ascertainment and live-birth prevalence. We consider three prior specifications concerning ascertainment and compare predicted maternal-age-specific prevalence under these three different prior specifications. The computations are carried out by using Markov chain Monte Carlo methods in which model parameters and missing data are sampled.     

Finite mixture models with concomitant information: assessing diagnostic criteria for diabetes

The World Health Organization (WHO) diagnostic criteria for diabetes mellitus were determined in part by evidence that in some populations the plasma glucose level 2 h after an oral glucose load is a mixture of two distinct distributions. We present a finite mixture model that allows the two component densities to be generalized linear models and the mixture probability to be a logistic regression model. The model allows us to estimate the prevalence of diabetes and sensitivity and specificity of the diagnostic criteria as a function of covariates and to estimate them in the absence of an external standard. Sensitivity is the probability that a test indicates disease conditionally on disease being present. Specificity is the probability that a test indicates no disease conditionally on no disease being present. We obtained maximum likelihood estimates via the EM algorithm and derived the standard errors from the information matrix and by the bootstrap. In the application to data from the diabetes in Egypt project a two-component mixture model fits well and the two components are interpreted as normal and diabetes. The means and variances are similar to results found in other populations. The minimum misclassification cutpoints decrease with age, are lower in urban areas and are higher in rural areas than the 200 mg dl^-1 cutpoint recommended by the WHO. These differences are modest and our results generally support the WHO criterion. Our methods allow the direct inclusion of concomitant data whereas past analyses were based on partitioning the data.     

基于GRPLS 回归的 中国经济增长影响因素分析

构造一种新的方法———岭- 偏最小二乘回归方法(它既有效消除了因素变量之间的多 重共线性,又克服了传统方法的不足,且使模型更加稳健,具有更强的预测和分析能力) ;并运 用广义岭- 偏最小二乘回归方法分析了我国经济增长的影响因素,为我国制订持续、快速增长 的经济政策提供了有益的参考.     

动力减振器最优参数的非线性回归和若干问题

本文采用最优化方法求得考虑生系统阻尼的动力减振器最优参数集，并对此参数集进行非线性回归，得到了便于动力减振器最优设计的回归曲线族。本文还对现有的主系统无阻尼时动力减振器最优参数公式进行了讨论，指出了这些公式的局限性，并根据本文的结果给出了应用范围更广泛的改进公式。     

Flow shop scheduling with deteriorating jobs under dominating machines

This paper addresses no-wait or no-idle flow shop scheduling problems with deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting time. A simple linear deterioration function is assumed and some dominating relationships between machines can be satisfied. It is shown that for the problems to minimize makespan or weighted sum of completion time, polynomial algorithms still exist, although these problems are more complicated than the classical ones. When the objective is to minimize maximum lateness or maximum tardiness, the solutions of a classical version may not hold.     

异质产品供应链定价控制权与零售商横向兼并效应分析

针对一部线性合约与供应商是否具有绝对定价控制权,比较分析零售商横向兼并集中度提高对消费者福利的影响.结果表明,(1)当供应商具有绝对定价控制权时,零售商横向兼并对消费者产生的影响取决于产品替代性程度大小:若替代性程度较高,则将产生有利影响,反之,将产生不利影响;(2)当供应商没有绝对定价控制权时,零售商横向兼并对消费者产生的影响取决于零售商兼并前的相对定价控制权强弱与兼并后的相对定价控制权增幅大小:若零售商在供应链中处于相对弱势地位,且零售商横向兼并使零售商的定价控制权增幅较大,则兼并将对消费者产生有利影响,否则,将对消费者产生不利影响.     

不同模型在财务预警实证中的比较研究

研究当前国内外公司财务困境预测问题的现状,寻找一套适合于我国企业的财务状况识别指标体系;然后依据该指标体系采用不同方法建立财务状况预测模型;最后,利用样本公司实际指标数据对各个模型的短期及中期预测效果进行了比较分析与实证研究。