Bias correction for parameter estimates of spatial point process models

When a spatial point process model is fitted to spatial point pattern data using standard software, the parameter estimates are typically biased. Contrary to folklore, the bias does not reflect weaknesses of the underlying mathematical methods, but is mainly due to the effects of discretization of the spatial domain. We investigate two approaches to correcting the bias: a Newton–Raphson-type correction and Richardson extrapolation. In simulation experiments, Richardson extrapolation performs best.     

Optimal designs for multivariate logistic mixed models with longitudinal data

This paper considers the optimal design problem for multivariate mixed-effects logistic models with longitudinal data. A decomposition method of the binary outcome and the penalized quasi-likelihood are used to obtain the information matrix. The D-optimality criterion based on the approximate information matrix is minimized under different cost constraints. The results show that the autocorrelation coefficient plays a significant role in the design. To overcome the dependence of the D-optimal designs on the unknown fixed-effects parameters, the Bayesian D-optimality criterion is proposed. The relative efficiencies of designs reveal that both the cost ratio and autocorrelation coefficient play an important role in the optimal designs.     

On the existence of maximum likelihood estimates for weighted logistic regression

The problems of existence and uniqueness of maximum likelihood estimates for logistic regression were completely solved by Silvapulle in 1981 and Albert and Anderson in 1984. In this paper, we extend the well-known results by Silvapulle and by Albert and Anderson to weighted logistic regression. We analytically prove the equivalence between the overlap condition used by Albert and Anderson and that used by Silvapulle. We show that the maximum likelihood estimate of weighted logistic regression does not exist if there is a complete separation or a quasicomplete separation of the data points, and exists and is unique if there is an overlap of data points. Our proofs and results for weighted logistic apply to unweighted logistic regression.     

Evidence of bias in the Eurovision song contest: modelling the votes using Bayesian hierarchical models

The Eurovision Song Contest is an annual musical competition held among active members of the European Broadcasting Union since 1956. The event is televised live across Europe. Each participating country presents a song and receive a vote based on a combination of tele-voting and jury. Over the years, this has led to speculations of tactical voting, discriminating against some participants and thus inducing bias in the final results. In this paper we investigate the presence of positive or negative bias (which may roughly indicate favouritisms or discrimination) in the votes based on geographical proximity, migration and cultural characteristics of the participating countries through a Bayesian hierarchical model. Our analysis found no evidence of negative bias, although mild positive bias does seem to emerge systematically, linking voters to performers.     

陕西省人口城市化Logistic模型及其应用——基于结构突变的理论分析

城市化是走向现代化的必经阶段,准确的城市化预测是进行经济、社会建设的基础。在结构突变理论的基础上,用Logistic模型对1978～2010年陕西城市化率进行分析。结论表明：1999年为陕西城市化率的结构突变点,说明城市化率的增长受到外部冲击的影响,分段以后的拟合优度明显提高。分别以阈值0.8和1进行分阶段构建的Logistic拟合精度明显提高,但阈值为1的精度更高,说明陕西城市化还在加速,预测表明到2030年陕西城市化率将达到70%左右。总体而言,从1984年到2030年为陕西省城市化的加速阶段。城市化加速阶段的住房问题、人口膨胀、环境恶化、交通拥挤、社会治安问题必须妥善解决。     

居民发展能力评估与差异比较——以甘肃省张掖市、甘南自治州为例

阿玛帝业森的能力理论是有关人类文化发展、福利经济学、社会政策研究的哲学论述,是有关个体福利和生活质量评估、社会整顿、政策制定和社会改革等的标准分析框架。本文在简要介绍阿玛帝亚森能力分析的概念和评估方法之后,采用社会学研究方法,通过问卷调查,以黑河流域张掖市与甘南自治州城市居民的能力分析测定为例,尝试在国内开展能力分析的定量研究,并比较影响两地区居民能力的主要因素,分析了提升个体能力,开展能力分析研究的重要意义。     

Identifying radon-prone building typologies by marginal modelling

Radon is a naturally occurring decay product of uranium known to be the main contributor to natural background radiation exposure. It has been established that the health risk related to radon exposure is lung cancer. In fact, radon is considered to be a major leading cause of lung cancer, second only to smoking. In this paper, we identified building typologies that affect the probability of detecting indoor radon concentration above reference values, using the data collected within two monitoring campaigns recently conducted in Northern Italy. This information is fundamental both in prevention, i.e. when the construction of a new building is planned and in mitigation, i.e. when a high concentration detected inside buildings has to be reduced. A spatial regression approach for binary data was adopted for this goal where some relevant covariates on the soil were retrieved by linking external spatial databases.     

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.     

农村中学生家长陪读影响因素研究

在文献研究的基础上提出研究假设,并利用问卷法和访谈法对179位调查对象进行资料收集,通过对调查资料的Logistic回归分析,探讨农村中学生家庭中哪些因素对家长选择陪读构成了显著性影响,得出研究结论：孩子的学习成绩、性格特征对陪读有显著影响;孩子所处的家庭环境对陪读有显著影响;父亲职业、母亲的文化水平对陪读有显著影响。     

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。