Diagnostics for elliptical linear mixed models with first-order autoregressive errors

For longitudinal time series data, linear mixed models that contain both random effects across individuals and first-order autoregressive errors within individuals may be appropriate. Some statistical diagnostics based on the models under a proposed elliptical error structure are developed in this work. It is well known that the class of elliptical distributions offers a more flexible framework for modelling since it contains both light- and heavy-tailed distributions. Iterative procedures for the maximum-likelihood estimates of the model parameters are presented. Score tests for the presence of autocorrelation and the homogeneity of autocorrelation coefficients among individuals are constructed. The properties of test statistics are investigated through Monte Carlo simulations. The local influence method for the models is also given. The analysed results of a real data set illustrate the values of the models and diagnostic statistics.     

标准化政策对主食产业化的影响

实现主食产业化发展，实行产品的标准化是关键。以豪特林（Hotelling）线形选址模型和塞洛普（Salop）的圆周模型为基础，根据具体情况进行修改后建立一个三阶段的博弈模型讨论主食企业和政府的行为问题。     

Optimal record-based statistical procedures for the two-parameter exponential distribution

There are a number of situations in which the experimental data observed are record statistics. In this paper, optimal confidence intervals as well as uniformly most powerful (MP) tests for one-sided alternatives are developed. Since a uniformly MP test for a two-sided alternative does not exist, generalized likelihood ratio and uniformly unbiased and invariant tests are derived for the two parameters of the exponential distribution based on record data. For illustrative purposes, a data set on the times between consecutive telephone calls to a company's switchboard is analysed using the proposed procedures. Finally, some open problems in this direction are pointed out.     

Multiple Time Series Modeling and Extended Sample Cross-Correlations

This article provides an expository account of the multivariate autoregressive moving average models and proposes an extended sample cross-correlation approach for practical model identification. An iterative model building procedure for applying these models to real data is discussed and demonstrated by analyzing the 5-series U.S. Hog Data.     

Comparison of causal effect estimators under exposure misclassification

Over the past decades, various principles for causal effect estimation have been proposed, all differing in terms of how they adjust for measured confounders: either via traditional regression adjustment, by adjusting for the expected exposure given those confounders (e.g., the propensity score), or by inversely weighting each subject's data by the likelihood of the observed exposure, given those confounders. When the exposure is measured with error, this raises the question whether these different estimation strategies might be differently affected and whether one of them is to be preferred for that reason. In this article, we investigate this by comparing inverse probability of treatment weighted (IPTW) estimators and doubly robust estimators for the exposure effect in linear marginal structural mean models (MSM) with G-estimators, propensity score (PS) adjusted estimators and ordinary least squares (OLS) estimators for the exposure effect in linear regression models. We find analytically that these estimators are equally affected when exposure misclassification is independent of the confounders, but not otherwise. Simulation studies reveal similar results for time-varying exposures and when the model of interest includes a logistic link.     

Nonparametric regression estimation in a null recurrent time series

We derive an asymptotic theory of nonparametric estimation for a time series regression model Z_t=f(X_t)+W_t, where {X_t} and {Z_t} are observed nonstationary processes, and {W_t} is an unobserved stationary process. The class of nonstationary processes allowed for {X_t} is a subclass of the class of null recurrent Markov chains. This subclass contains the random walk, unit root processes and nonlinear processes. The process {W_t} is assumed to be linear and stationary.     

技术进步对我国经济增长作用的实证分析

为考察改革开放以来我国技术进步对经济增长贡献份额的变化情况，选用1979—2003年的相关数据进行实证分析。研究表明，改革开放以来我国技术进步对经济增长的贡献率偏低，经济增长主要是靠资本投入和劳动投入（特别是资本投入）来拉动的。因此，今后应不断增强我国企业的技术吸收能力和自主创新能力，实现从粗放型增长方式到集约型增长方式的转变，增强技术进步对经济增长的促进作用。     

缝洞型油藏储集体分类建模方法研究

为了表征缝洞型碳酸盐岩油藏储集体类型多样、尺度差异大、空间分布规律复杂的特征，采用"分级分类、岩溶相控、多类型融合"的方法，分别对不同类型缝洞储集体的规模大小、外部几何形态及内部属性特征进行建模，建立了基于岩溶成因的融合原则，实现了不同类型缝洞储集体的融合，并通过新钻井验证了模型可靠性。结果表明，该方法适用于此类强非均质性油藏的地质建模，能够有效表征不同类型储集体及属性参数的空间分布特征。基于模型，细化了XX单元的储量构成，其中，溶洞储量占63.1%，溶蚀孔洞储量占34.5%，大尺度裂缝储量占2.4%。该模型在油藏数值模拟中取得了较好的拟合效果和模拟结果。     

私家车增长logistic回归分析模型

为汽车销售行业制定营销策略提供借鉴,也为私家车消费者理性决策提供参考,通过分析购置私家车的主要影响因素家庭因素、停车条件、交通环境、养车费用与购车决策之间的相关关系,运用SPSS软件进行模拟运算,建立了私家车购置logistic回归分析模型,应用该模型对私家车增加进行了预测,并对私家车购置决策提供了可参考的方法。     

教科书变革对教学方式影响的质性研究——以新课程义务教育历史教科书为例

对于教科书问题,目前过多的集中在教教科书与用教科书教以及教科书理论研究层面,而在真实的课堂教学中关注教科书研究问题却少有问津。课程标准指导下的新教材,其内涵已融入新的理念。基于个案研究分析以了解在真实的历史教学活动中教科书是如何影响教师的教授和学生的学习方式,换一种视角来探讨研究新课程下教科书变革问题比起纯理论说明也许会给我们今后使用或研究教科书更多启示。