城市公共交通出行者交通信息选择行为研究

先进的交通信息服务系统建设是我国城市交通可持续发展的必由之路。文章基于大连市公共交通出行信息需求专项调查,通过多维度频率分布研究,对不同个人属性、信息服务特征等条件下公共交通出行者的交通信息内容需求进行分析,进一步建立公共交通出行者交通信息选择binary logistic模型,对公共交通出行者交通信息选择行为进行研究。研究显示,公共交通出行者交通信息内容需求因个人属性、信息服务特征等因素存在较大差别,交通信息内容对公共交通出行者交通信息选择行为存在不同程度的影响。最后,文章基于实证研究结果,提出面向城市公共交通出行者的交通信息服务系统规范化建设的相关策略。     

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。     

Foot-and-Mouth Disease Entrance Assessment Model Through Air Passenger Violations

This article aims to construct a risk model for the prediction of foot-and-mouth disease (FMD) entrance caused by passengers who illegally carry meat products of cloven-hoofed animals through international airports into a country. The risk that meat contaminated with the FMD virus is formulated as the probabilities of FMD factor events (the prevalence of FMD), the commodity factor event (the transportation, storage, and distribution (TSD) factor event), and the passenger event. Data used for analysis were records of illegal meat product carriers from areas A and B intercepted at an international airport in Taiwan. A risk model was proposed to simulate the probability distributions in disease prevalence, probability of FMD virus existing in the meat products after meat processing, and estimation of survival of virus and time period for TSD. The probability of the passenger event was hypothesized with the odds of intercepted passengers and estimated via logistic regression. The results showed that the odds of passengers being intercepted by beagles were higher than those intercepted by Customs. By conducting Monte Carlo simulations, the probability of FMD virus risk caused by FMD factors from area A was 149 times lower than that from area B. The probability of FMD virus risk caused by the passenger event from area A was four times lower than the corresponding probability from area B. The model provides a contribution to FMD prevention and can be a reference for developing models of other diseases.     

Comparative Study of Generalized Estimating Equations and Logistic Regressions on Different Sample Sizes and Correlation Levels

In this study, it was aimed to determine accuracy of generalized estimating equations versus logistic regressions on different correlation levels and sample sizes. For this aim, two methods were compared with different sample sizes 10, 25, 50 and 100 and correlation levels 0.0, 0.3, 0.5 and 0.8. Result of this study showed that using generalized estimating equations could be preferred versus logistic regression when the sample size is over than 25 and correlation level is higher than 0.3 on data taken from studies with repeated measurements, but logistic regression could be better when the autocorrelations do not exist.     

基于主成分logistic回归模型的餐饮商务信息意识研究

数据挖掘技术日趋成熟,广泛应用于金融、地产、投资、评估等各个领域。数据挖掘技术亦可应用于餐饮业,为其经营决策做出分析。其他领域的数据挖掘的成功案例也可以引用到餐饮行业中。本文对餐饮人士在餐饮商务中是否具备信息意识、对信息意识的重视程度进行调查,利用数据挖掘中主成分分析和 logistic 回归处理和分析收集来的数据,从而说明数据挖掘在餐饮业管理中的重要意义,反映餐饮人士信息意识状况。利用数据挖掘技术对餐饮商务资讯进行管理势必提高企业效率和盈利水平,促进餐饮业健康稳定的发展。     

A new heavy-tailed distribution defined on the bounded interval: the logit slash distribution and its application

This paper proposes a new heavy-tailed and alternative slash type distribution on a bounded interval via a relation of a slash random variable with respect to the standard logistic function to model the real data set with skewed and high kurtosis which includes the outlier observation. Some basic statistical properties of the newly defined distribution are studied. We derive the maximum likelihood, least-square, and weighted least-square estimations of its parameters. We assess the performance of the estimators of these estimation methods by the simulation study. Moreover, an application to real data demonstrates that the proposed distribution can provide a better fit than well-known bounded distributions in the literature when the skewed data set with high kurtosis contains the outlier observations.     

Diagnostics of multiple group influential observations for logistic regression models

In this paper, two new multiple influential observation detection methods, GCD.GSPR and mCD*, are introduced for logistic regression. The proposed diagnostic measures are compared with the generalized difference in fits (GDFFITS) and the generalized squared difference in beta (GSDFBETA), which are multiple influential diagnostics. The simulation study is conducted with one, two and five independent variable logistic regression models. The performance of the diagnostic measures is examined for a single contaminated independent variable for each model and in the case where all the independent variables are contaminated with certain contamination rates and intensity. In addition, the performance of the diagnostic measures is compared in terms of the correct identification rate and swamping rate via a frequently referred to data set in the literature.     

The effect of small sample on optimal designs for logistic regression models

Asymptotic methods are commonly used in statistical inference for unknown parameters in binary data models. These methods are based on large sample theory, a condition which may be in conflict with small sample size and hence leads to poor results in the optimal designs theory. In this paper, we apply the second order expansions of the maximum likelihood estimator and derive a matrix formula for the mean square error (MSE) to obtain more precise optimal designs based on the MSE. Numerical results indicate the new optimal designs are more efficient than the optimal designs based on the information matrix.     

透过海尔物流浅析中国物流市场

海尔的“物流推进本部”成为中国物流业界关注的亮点，面对加入WTO后中国物流市场面临的机遇和挑战，中国的物流企业应认清形势，兼收并蓄，在政府的支持下，积极转变物流职能，提高服务质量，增强竞争能力。     

农用承包地流转意愿的实证研究--基于福建省六地市农户问卷调查

从农户意愿角度,以福建省农民的农用承包地为研究对象,对影响农户承包地流转的因素进行分析,通过实地调查和问卷调查的形式收集到影响农户流转承包地的样本数据,并对通过建立二元Logistic模型对各个因素的显著性进行检验。通过实证研究发现,户主受教育程度、户主的职业、农户家庭的人口、家庭的收入主要来源、承包地面积和农户流转承包地的租金水平是农户流转承包地的显著性影响因素,其中户主受教育程度、家庭的收入主要来源、承包地面积和租金水平是正向影响,户主的职业和农户家庭的人口是负向影响。根据研究的结论提出相应的政策建议。