基于多因素灰色模型的物流需求量预测

物流需求量受多种因素的影响,很多因素无法准确掌握.文章通过咨询专家和客观分析,选定GDP增长量、消费品零售总额、进出口总额等七大因素为影响物流需求量的关键因素.然后,将体现灰色GM(1,1)模型和多元线性回归模型优点的多因素灰色预测模型应用于河南省物流需求量的预测实证研究中,为物流需求量的预测提供了一种可靠的科学方法.     

基于主成分分析基础上的中国蔬菜家庭消费预测

文章在对中国蔬菜家庭消费的现状进行论述后,通过主成分分析法分析影响中国蔬菜家庭消费的五个因素,再利用回归得出城镇和农村居民的不同家庭人均蔬菜消费量的模型.在此基础上,以城镇人口和农村人口为因变量,建立人口的时序模型.结合这两个模型对我国蔬菜的家庭消费量,以及全国蔬菜家庭消费市场总容量进行未来年份的预测,以期为中国蔬菜产业发展中的政策制定和战略调整提供依据.     

我国区域物流发展预测

物流需求预测是政府有关部门制定物流规划和建设物流基地的决策依据,也是第三方物流企业发展物流业务的重要前提.本文在对物流需求变化的影响因素分析以及对物流需求指标选取的基础上,采用回归模型、灰色预测方法、加权组合模型对湖北物流需求进行预测.使最终的预测结果收敛于一个较窄的区间内,这种预测模型较完全反映物流需求量的变化规律.     

湖北省蔬菜产业发展对农村居民可支配收入影响研究

文章选取湖北省蔬菜面积、蔬菜产量、蔬菜出口量、蔬菜出口额、蔬菜加工产值等5个因子来与农村居民可支配收入建立评价模型,采用多元回归分析的方法对湖北省2002-2013年农村居民可支配收入的影响因素进行了回归分析,运用多重共线性检验、修正多重共线性、异方差性检验等多种方法对模型进行了检验和修正,模型预测结果表明实际值与预测值基本一致.因此,湖北省蔬菜产业农村居民可支配收入与蔬菜出口量、蔬菜加工产值存在显著性相关关系.     

基于系统动力学的中国石油需求系统模型及预测

建立了基于系统动力学的我国石油需求系统模型,然后利用GM(1.1)灰色模型对部分因素进行预测,再将灰色系统模型的预测值导入模型.从而对2008～2020年我国石油消费对外依存度和石油需求量进行了预测.预测结果表明,我国石油消费对外依存度以年均1.51%的速度增长,2020年战略石油储备完成后,石油消费对外依存度将达到62.5%.我国石油总消费量将2.5%的速度增长,到2020年将达到5.28亿吨.通过政策模拟,预测了不同经济发展速度下我国的石油需求量,结果表明,经济的发展速度对我国的石油需求量影响比较大.     

我国蔬菜产业生产效益影响因素的实证分析

文章以山东省苍山县为例,通过构建回归模型分析了我国蔬菜生产效益的主要影响因素,结果显示:在苍山县蔬菜经济发展的初期,蔬菜价格指数、劳动力、露地蔬菜播种面积、蔬菜运输人员、化肥、成灾面积、政府公共投资是苍山县蔬菜生产效益的主要影响因素;在其快速发展时期,蔬菜价格指数,加工企业、集中度、大棚蔬菜播种面积、批发市场、运输动力、通讯、排灌、化肥和公共投资是主要影响因素。并提出政策建议。     

城市蔬菜品种安全指数的预测分析

文章以2007年1～4月的菜心品种安全指数为样本,对于落在不同监测预警区域的蔬菜品种安全指数,运用干预影响模型和时序平滑模型进行预测分析.结果表明,这两种不同模型的运用对蔬菜品种安全指数的拟舍和预测效果都较好,准确性高、误差小.     

企业技术创新能力的评价模型

文章提出了企业技术创新能力评价的因果关系模型,利用结构方程模型对评价指标间的因果关系进行了建模和求解。实证研究表明,模型能够有效描述指标间的因果关系、准确定位企业技术创新能力的关键影响因素,为评价和改进企业技术创新能力提供了有力依据。     

Granger因果关系检验的模型选择与相关策略研究

运用Granger因果关系检验识别确定经济变量间因果关系是经济研究中极为常见的分析模式,然而在具体应用时,Granger因果关系检验的功效会受到模型形式选择与检验策略因素的影响,为此,解析了Granger因果关系检验的水平型VAR、差分型VAR、VEC三种模型形式选择的基本原理,探讨了与模型选择相关的四大检验策略,即变量个数选择、滞后阶数选择、变量单整性检验、协整空间维数选择,并给出了Granger因果关系检验相对稳妥的实践操作程序。     

回归预测中应注意的问题

文章从数据的收集与处理、因果关系分析、模型的建立与参数估计、模型的检验和预测等方面论述了回归预测中应注意的问题.     

Analysis of changes in mortality in Poland

Mortality rates for both sexes for 5- and 10-year age intervals are analyzed for the years 1960-1983 for various localities of Poland. The author notes a decline in mortality since 1966, and provides new estimates of that trend. Some problems concerning the data are also considered.     

中国工资差异变动的分解

使用CHNS（中国健康与营养调查）提供的工资横截面数据,通过Oaxaca-Blinder分解方法,在分位数回归的基础上,分别以总样本、东部样本和中西部样本,对1989—2006年、1989—1997年和1997—2006年三个时间段的工资差异的变动进行分解,研究发现：在大多数情况下,解释变量的结构效应小于解释变量的价格效应;在方向上,结构效应与工资差异变动的方向相反,而价格效应与工资差异变动方向相同;工资差异的变动无论是结构效应引起的还是价格效应引起的,都主要发生在工资分布的低端;作为重要解释变量的技能偏向型技术进步引起的工资差异变动,主要发生在工资分布的高端;在不同时间段和不同样本下,解释变量对工资差异变动的影响程度存在差异。     

Estimation of population product in presence of non-response in successive sampling

The design of this paper is to examine the problem of estimation of finite population product in mail surveys for the current occasion in the context of sampling on two occasions is attempted when there is non-response on both the occasions. Estimators for the current occasion are derived as a particular case when there is non-response on first and second occasion only. The gain in efficiency of the proposed estimate over the direct estimate using no information gathered on the first occasion is computed. The proposed strategy has been compared with other estimators. An empirical study is carried out to study the performance of the proposed strategy.     

Design of experiments in the presence of errors in factor levels

This paper is concerned with the statistical properties of experimental designs where the factor levels cannot be set precisely. When the errors in setting the factor levels cannot be measured, design robustness is explored. However, when the actual design could be measured at the end of the investigation, its optimality is of interest. D-optimality could be assessed in different ways. Several measures are compared. Evaluating them is difficult even in simple cases. Therefore, in general, simulations are used to obtain their values. It is shown that if D-optimality is measured by the expected value of the determinant of the information matrix of the experimental design, as has been suggested in the past, on average the designs appear to improve with the variance of the error in setting the factor levels. However, we argue that the criterion of D-optimality should be based on the inverse of the information matrix. In this case it is shown that the experiment could be better or worse than the planned one. It is also recognized that setting the factor levels with error could lead to an increased risk of losing observations, which on its own could reduce considerably the optimality of the experimental designs. Advice on choosing the design region in such a way that such a risk is controlled to an acceptable level is given.     

利用因子分析法浅析我国健康经济发展状况

在经济发展促进人们收入水平不断提高的同时,经济学界引入了一种全新的理念即"健康经济"来衡量和评价经济的发展。文章利用因子分析的方法来剖析我国各个省市在促进"健康经济"发展上的不同表现,并提出一些相关的政策建议,为促进我国各省市"健康经济"的发展提供一定的理论依据。     

Evaluation of Response Surface Designs in Presence of Errors in Factor Levels

Experimenters are often confronted with the problem that errors in setting factor levels cannot be measured. In the robust design scenario, the goal is to determine the design that minimizes the variability transmitted to the response from the variables’ errors. The prediction variance performance of response surface designs with errors is investigated using design efficiency and the maximum and minimum scaled prediction variance. The evaluation and comparison of response surface designs with and without errors in variables are developed for second order designs on spherical regions. The prediction variance and design efficiency results and recommendations for their use are provided.     

Estimation of regression parameters in the presence of outliers in the response

In this paper, we consider a regression model with non-spherical covariance structure and outliers in the response. The generalized least squares estimator obtained from the full data set is generally not used in the presence of outliers and an estimator based on only the non-outlying observations is preferred. Here we propose as an estimator a convex combination of the full set and the deleted set estimators and compare its performance with the other two.     

对《国际服务贸易统计制度》中服务贸易统计框架的分析与评价

 2010年8月1日新版《国际服务贸易统计制度》开始在中国正式实施,我国的服务贸易统计框架从制度上得以确定。本文首先对《制度》所构建的服务贸易统计框架进行介绍,然后通过与《国际服务贸易统计手册》的比较,找出其与《手册》相关建议的差异之处并结合我国服务贸易统计存在的问题提出相应的建议。     

Statistical Analysis of Heat Waves in the State of Victoria in Australia

The recent blistering heat waves of 2009 in the state of Victoria in Australia were so unprecedented in terms of duration and intensity that society was largely unprepared. These heat waves caused serious health, social and economic problems. In this paper, the daily maximum temperatures at ten selected stations are studied. Auto‐regressive integrated moving‐average models are used to prewhiten the time series. Uncorrelated, non‐normal and heavy‐tailed residuals are analyzed by means of a new skew t‐mixture distribution. The number of mixture components is effectively determined by an innovative penalisation procedure. It is shown that the resulting skew t‐mixture models provide an acceptable fit in all cases. Possible future temperature patterns are obtained through simulation. It is forecast that the average duration of high temperature episodes will increase by two to three days per year and a new eight‐year high temperature level is very likely in the coming few years. The relationship between heavy tail behaviour of the fitted distribution and heat waves is noteworthy.