有错检验情况下标准型抽样方案的设计

本文给出了在有错检验情况下标准型抽样方案的设计方法，讨论了误检概率ｐ，ｐ′对抽样方案的影响，并给出抽样方案的实际应用。     

分位数回归及应用简介

文章介绍了分位数回归法的概念、算法及主流统计软件R和SAS计算时的语法,并通过实例与以普通最小二乘法为基础的线性回归进行了对比,展现了分位数回归的巨大魅力。     

存在战略购买需求的定价、供给、机制选择和配给研究

本文研究存在战略购买需求的易逝资产销售策略问题。垄断厂商基于利润最大化目标确定易逝资产定价、供给、机制选择和配给策略,战略消费者通过锚定预期价格安排战略购买时机。不同于通常基于效用理论研究定价的思路,本文首先基于锚定效应和跨期价格均衡思想探寻不同战略等待购买规模的市场预期需求曲线和动静态定价区域;其次在众多预期需求曲线中寻找市场有效定价前沿（即有效预期需求曲线）;再次在利润曲面上找出与有效定价前沿对应的容量扩展线（即最大利润曲线）;最后沿容量扩展线和有效定价前沿搜寻最大期望利润及相应策略。研究表明,消费者保留价异质和需求不确定性是动态定价和战略购买存在的根本原因;市场在不同战略等待购买规模状态拥有不同预期需求曲线,最大战略等待购买规模状态预期需求曲线是市场有效定价前沿。动静态定价机制各有其所适用的容量和价格空间,消费者保留价水平和战略消费者规模决定动态定价空间大小,随机需求分布差异只影响动态定价空间形状（即影响需求弹性）。在跨期价格均衡区域内,提价和扩容都会加剧消费者战略购买程度,供给越大定价往往越低。战略购买不仅会降低厂商供给、定价和利润水平,改变不同类型消费者之间高低价购买机会,甚至还可能影响定价机制选择和配给策略。压缩过度供给和虚高价格空间可降低战略购买导致的利润损失。本文研究结果可为考虑消费者行为的需求价格理论研究和运营管理实践提供参考。     

生态功能区域农村土地流转行为影响因素研究

厘清农户土地流转行为的主要影响因素,推进流转意愿与流转行为相匹配,对于生态功能区域提升土地利用效率、保障生态用地供给具有重要意义。基于河北省农户调研数据,将二元Logistic回归模型和ROC曲线相结合,深入分析农户土地流转行为的影响因素,并依据ROC曲线检验模型效果和界定最佳预测阈值。模型结果显示ROC曲线的Youden指数为32.7%,对应的预测阈值为0.41,模型效果较为良好,研究结果表明家庭人口规模、承包土地规模、主要收入来源、土地归属认知、村庄地形、村庄类别、租金是影响农户土地流转行为的显著性影响因素,农户土地流转行为发生的影响因素并不限于经济因素的考量。     

中国股票市场的信息反应曲线和股票价格波动的非对称性

股票价格波动对于市场信息的反应过程具有非对称性。通过利用多种非对称性GARCH 模型,描述和检验了沪市股票日收益率序列的条件波动性,并通过对股票市场信息影响曲线的分析,发现沪市股票价格波动中存在显著的非对称性反应。这说明股市波动对于不同的政策干预和信息冲击具有不同程度的反应,“利好消息”对股市的刺激作用仍然需要其他市场干预的配合才能发挥出来。     

从“凯恩斯效应”到“阿米曲线”——政府规模与经济增长关系的非线性转向

政府规模与经济增长之间的关系问题是宏观经济研究中的核心问题之一.关于两者关系的传统研究往往以线性假定为基础,所以实证结果出现了巨大的差异.这种现象促使研究者从非线性角度重新审视政府规模与经济增长之间的关系.“巴罗法则”在内生增长框架内为政府规模与经济增长关系研究提供了一个标准的分析框架,揭示了两者之间的倒“U”关系.而“Armey曲线”不仅非常直观地表达了政府规模与经济增长之间的非线性关系,同时还指出这种非对称关系的非对称性质,具有很强的总结性和政策指导意义.     

Testing hypotheses for the growth curve model when the data are incomplete

Kleinbaum (1973) developed a generalized growth curve model for analyzing incomplete longitudinal data. In this paper the small sample properties of several related test statistics are investigated via Monte Carlo techniques. The covariance matrix is estimated by each of three non-iterative methods. The null and non-null distributions of these test statistics are examined.     

A robust and efficient estimation method for nonparametric models with jump points

Nonparametric models with jump points have been considered by many researchers. However, most existing methods based on least squares or likelihood are sensitive when there are outliers or the error distribution is heavy tailed. In this article, a local piecewise-modal method is proposed to estimate the regression function with jump points in nonparametric models, and a piecewise-modal EM algorithm is introduced to estimate the proposed estimator. Under some regular conditions, the large-sample theory is established for the proposed estimators. Several simulations are presented to evaluate the performances of the proposed method, which shows that the proposed estimator is more efficient than the local piecewise-polynomial regression estimator in the presence of outliers or heavy tail error distribution. What is more, the proposed procedure is asymptotically equivalent to the local piecewise-polynomial regression estimator under the assumption that the error distribution is a Gaussian distribution. The proposed method is further illustrated via the sea-level pressures.     

Bayesian Design of Special Type of Double Sampling Plans for Compliance Testing

Bayesian acceptance sampling plans, which utilize prior information on the process variation, can be employed as an alternative to conventional types of plans for taking decisions on the disposition of submitted lots. A special type of double sampling inspection plans by attributes with small acceptance numbers using Bayesian methodology is presented in this paper emphasizing its significance over small acceptance number single sampling plans. The procedures for designing such sampling plans for specified degree of discrimination which would ensure protection to the producer and consumer are discussed with illustrations under the conditions for the application of gamma-Poisson distribution.     

Developmental Patterns in Marital Satisfaction: Another Look at Covenant Marriage

This study investigated differences in the trajectory of marital satisfaction in the first 7 years between couples in covenant versus standard marriages. The authors analyzed data on 707 Louisiana marriages from the Marriage Matters Panel Survey of Newlywed Couples, 1998–2004, using multivariate longitudinal growth modeling. When the sample was restricted to couples who remained married over the duration of the study, a marginal benefit of covenant status was found for husbands. This effect was largely accounted for by covenant husbands' more extensive exposure to premarital counseling. The linear decline in marital satisfaction over time that obtained for both husbands and wives was not, however, any different for covenant marriages versus standard marriages. Couples characterized by more traditional attitudes toward gender roles were significantly less satisfied than others. High premarital risk factors, initial uncertainty about marrying the spouse, and the presence of preschool‐age children in the household were all corrosive of marital satisfaction at any given time.