On the Breslow–Holubkov estimator

Breslow and Holubkov (J Roy Stat Soc B 59:447–461 1997a) developed semiparametric maximum likelihood estimation for two-phase studies with a case–control first phase under a logistic regression model and noted that, apart for the overall intercept term, it was the same as the semiparametric estimator for two-phase studies with a prospective first phase developed in Scott and Wild (Biometrica 84:57–71 1997). In this paper we extend the Breslow–Holubkov result to general binary regression models and show that it has a very simple relationship with its prospective first-phase counterpart. We also explore why the design of the first phase only affects the intercept of a logistic model, simplify the calculation of standard errors, establish the semiparametric efficiency of the Breslow–Holubkov estimator and derive its asymptotic distribution in the general case.     

An improved and efficient biased estimation technique in logistic regression model

Abstract

In this article, we propose a new improved and efficient biased estimation method which is a modified restricted Liu-type estimator satisfying some sub-space linear restrictions in the binary logistic regression model. We study the properties of the new estimator under the mean squared error matrix criterion and our results show that under certain conditions the new estimator is superior to some other estimators. Moreover, a Monte Carlo simulation study is conducted to show the performance of the new estimator in the simulated mean squared error and predictive median squared errors sense. Finally, a real application is considered.     

农户小额贷款违约影响因素研究

基于江苏北部某地区2007—2015年18万条真实农户大样本小额贷款记录,结合当地及全国CPI、GDP、第一产业产值、地区农业生产资料价格指数等宏观经济指标,采用基于最大似然估计逐步进入法的Logistic模型,筛选对农户违约概率影响较为显著的指标,之后对各指标经济含义进行了解释并对模型进行稳健性分析。研究发现：信用水平指标与农户的真实违约情况关联不显著,意味着当地信贷机构对贷款农户的贷前内部信用评级不能有效地预测农户的信用风险;利率、性别、婚姻状况、职业、教育等微观指标对信用风险有较大影响;全国范围的GDP和CPI、江苏农业生产资料价格指数、滞后一期的当地第一产业GDP等宏观指标也对信用风险具有预测作用; Logistic模型在不平衡数据集上,依然能保持较好的分类精度。     

A quick response production strategy to market demand

The reason for considering the quick response production strategy to market demand is due to the rapid technology change, which results in decreasing market price and obsolescence. This study considers a production strategy of locating final production line in response to the changes in market demand and the continuous deterioration in stock. The demand rate is assumed to decrease exponentially with time while the price is assumed to decrease linearly with time. The purpose of this study is to derive the most economical site of final-production line that assembles products with short life cycle. The model considered in this research takes into account the sales revenue, the deteriorating cost, the carrying cost, the variable cost and the fixed cost of production. Although there is a higher labour and material cost when the production site is located near market point, the total profit increases due to quicker responsive time, smaller import tax, lower inventory and lesser deteriorating cost.     

基于非线性-主成分Logistic回归的会计舞弊识别研究

混沌理论认为,人类行为大多具有非线性特征。会计舞弊属于行为会计的研究范畴,而传统上基于统计理论构建的舞弊识别模型大多受限于线性约束假设,可能存在模型设定偏误和信息提取不充分的缺陷。以沪深A股受到监管处罚的上市公司及其配对公司为样本,借鉴Taylor展开式的非线性思想,并使用主成分分析消除变量多重共线性,构建了非线性-主成分Logistic回归的会计舞弊识别模型。与线性回归模型对比发现,前者具有更高的舞弊识别正确率,模型拟合度更优。应用这一模型有助于更加充分提取舞弊识别信息,提高舞弊识别效率。     

人口增长的Logistic模型及其应用研究

]相对于其他预测模型而言 ,L ogistic模型解决了对增长率变动时的人口发展过程的模拟问题 ,特别适宜于模拟人口发展速度递减、逐渐趋于零增长时的情况 ,适合于计划生育工作比较稳定、抓得比较紧的地区。但本模型缺乏人口转换为负增长地区的预测能力 ,而且计算的人口极值是相对的     

人口预测常用模型及其比较分析

人口问题一直是制约我国经济快速发展的关键因素之一，准确预报人口增长是人口研究的一个热点．本文根据（2005年中国统计年签》公布的人口数据分别建立了CM（1，1）模型、Leslie模型、Logistic模型来预测我国未来人口发展的趋势，并比较了这几个模型预测的优缺点．     

Prior elicitation, variable selection and Bayesian computation for logistic regression models

Bayesian selection of variables is often difficult to carry out because of the challenge in specifying prior distributions for the regression parameters for all possible models, specifying a prior distribution on the model space and computations. We address these three issues for the logistic regression model. For the first, we propose an informative prior distribution for variable selection. Several theoretical and computational properties of the prior are derived and illustrated with several examples. For the second, we propose a method for specifying an informative prior on the model space, and for the third we propose novel methods for computing the marginal distribution of the data. The new computational algorithms only require Gibbs samples from the full model to facilitate the computation of the prior and posterior model probabilities for all possible models. Several properties of the algorithms are also derived. The prior specification for the first challenge focuses on the observables in that the elicitation is based on a prior prediction y ₀ for the response vector and a quantity a ₀ quantifying the uncertainty in y ₀. Then, y ₀ and a ₀ are used to specify a prior for the regression coefficients semi-automatically. Examples using real data are given to demonstrate the methodology.     

The long-term pattern of adult mortality and the highest attained age

Recent new data on old age mortality point to a particular model for the way in which the probability of dying increases with age. The model is found to fit not only modern data but also some widely spaced historical data for the 19th and 17th centuries, and even some estimates for the early mediaeval period. The results show a pattern which calls for explanation. The model can also be used to predict a probability distribution for the highest age which will be attained in given circumstances. The results are relevant to the current debate about whether there is a fixed upper limit to the length of human life.     

品牌形象对购买意愿影响的性别差异研究——以自用化妆品市场为例

本文以自用化妆品消费者为研究对象,通过调查问卷收集数据并利用因子分析和Logistic回归的方法对数据进行分析处理,由此探讨了品牌形象对消费者购买意愿影响的性别差异。研究结果表明,厂商或企业为了更好地提高其顾客的购买意愿,要区别对待不同性别的消费者,做到有目的、有计划、有组织地建立其产品的品牌形象,从而使企业或厂商在竞争中立于不败之地。