Testing equality of two normal covariance matrices with monotone missing data

Abstract

The problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example.     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

Efficient Estimation in Heteroscedastic Partially Linear Varying Coefficient Models

This article considers statistical inference for the heteroscedastic partially linear varying coefficient models. We construct an efficient estimator for the parametric component by applying the weighted profile least-squares approach, and show that it is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator reaches the semiparametric efficiency bound. Simulation studies are conducted to illustrate the performance of the proposed method.     

川东北地区须家河组二段储层差异性分析

随着勘探程度的深入，为了扩大四川盆地天然气勘探领域、寻找新的勘探接替区，四川盆地的勘探区域由盆内逐渐向盆缘延伸。在这种背景下，川东北地区须家河组二段相继取得新的勘探成果，但在勘探开发过程中逐渐暴露了诸如区块之间气井产能差异大，储层的碎屑组分、结构及厚度、物性、孔隙结构差异明显等问题，制约了勘探开发的步伐。针对上述问题，根据岩芯观察描述、分析化验资料及测井解释成果，从沉积、成岩方面入手，对比剖析了川东北龙岗和营山地区须二段储层特征的差异性及其成因，认为远离物源区和高能水体的反复淘洗是造成储层差异性的首要因素，强烈的压实作用和多期石英加大对储层差异性起关键作用，自生绿泥石衬边胶结和长石选择性溶蚀最终决定了储层差异性。从而解释了气藏勘探开发中遇到的诸多问题，对有效指导该区的下一步勘探开发工作具有重要意义。     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

Conditional time-dependent nonparametric estimators with an application to healthcare production function

ABSTRACT

By using the probabilistic framework of production efficiency, the paper develops time-dependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.     

京津冀节能减排政策措施的差异与协同研究

在对京津冀1981年以来节能减排政策措施进行量化处理的基础上,建立针对节能减排政策措施有效性的计量模型,分析了京津冀节能减排政策措施的演变状况,并探究京津冀节能减排政策措施对其节能减排效果影响的差异性.研究结果表明:京津冀节能减排政策颁布经历了早期各年份相对零散、缺乏连续性到新世纪以来政策颁布数量显著增多、政策总体力度逐渐增大的过程,但三地政策总效力的增加主要是由于节能减排政策颁布数量增多引起的;京津冀三地在政策的制定过程中更多的是趋于实现短期目标,政策整体缺乏系统性和权威性;人事措施、行政措施、引导措施、财税措施、金融措施等不同节能减排政策措施对京津冀节能和减排的有效性具有明显的差异;三地对不同政策措施的使用方式、使用程度方面存在明显的差异,这对京津冀协同推进节能减排的治理工作提出挑战.论文还从京津冀完善单一节能减排政策措施的使用、加强市场手段的应用及京津冀区域协同治理等方面提出了相应政策建议.     

双波长比值法测定水杨酸、间苯二酚、对氨基苯甲酸的含量

依据水杨酸、间苯二酚、对氨基苯甲酸三组分的比值光谱特征,以对氨基苯甲酸为干扰组分,选择241nm、278nm作为测定水杨酸的波长;以水杨酸作为干扰组分,选择214nm、240nm作为测定间苯二酚的波长;以间苯二酚作为干扰组分,选择222nm、279nm作为测定对氨基苯甲酸的波长.结果显示,水杨酸浓度在1~80mg/L,基本二酚浓度在0.8~40mg/L,对氨基苯甲酸浓度在0.4~40mg/L范围内具有良好的线性关系.本方法具有测定波长少,光谱分离能力强、计算简单、能在低档分光光度计上实现、易于推广等特点.     

异质品双渠道供应链下制造商的渠道决策研究

研究由两个制造商、两个零售商以及消费者组成的双渠道供应链，制造商的最优产品分销渠道策略问题，通过构建Stackelberg主从动态博弈模型，分析制造商在不同渠道选择下的产品质量水平及定价决策，消费者三种不同渠道偏好下渠道竞争和品牌竞争激烈程度对制造商渠道选择均衡结果及帕累托最优选择的影响，以及对产品质量水平、产品价格、制造商及零售商利润的影响.研究表明：品牌和渠道双重竞争下，两种竞争之间存在相互作用的关系，并共同影响制造商最终渠道选择，制造商通过权衡价格决策的后动优势与消费者渠道偏好对其利润的贡献选择是否开辟双渠道，产品价格与产品质量水平正相关，与产品的替代率负相关，产品质量水平对渠道价格的影响程度等于消费者对该渠道的偏好程度.当消费者偏好某一渠道时，制造商可在该渠道上的产品采取优质高价策略，但渠道上产品性价比降低，当品牌竞争越激烈，产品价格越低，对制造商和零售商的利润挤压越严重.