Alternative covariance estimates in a replicated measurement error model with correlated,heteroscedastic errors

The article concerns covariance estimates in a replicated measurement error model with correlated, heteroscedastic errors. Freedman has conjectured that using more of the data will improve estimates of covariance matrices and result in a more efficient estimate of the coefficient of the regression model. The paper confirms the conjecture asymptotically for the case that all random variables are normally distributed, but the gain is not substantial.     

On the estimation of variance components in stability analysis

Chow and Shao (1989, 1991) indicated that the presence of batch-to-batch variation has an impact on the determination of drug shelf-life in stability studies. In this paper, we propose two unbiased estmators for batch-to-batch variation. The proposed estimators are compared in terms of their corresponding variances. An example concerning a stability study is discussed to illustrate the use of the proposed estimators.     

Marginally oversaturated designs

A special class of supersaturated design, called marginally over saturated design (MOSD), in which the number of variables under investigation (k) is only slightly larger than the number of experimental runs (n), is presented. Several optimality criteria for supersaturated designs are discussed. It is shown that the resolution rank criterion is most appropriate for screening situations. The construction method builds on two major theorems which provide an efficient way to evaluate resolution rank. Examples are given for the cases n=8, 12, 16, and 20. Potential extensions for future work are discussed.     

An alternative proof for a version of cochran's theorem under elliptical settings

For an elliptically contoured n × p random matrix Y with mean μ and covariance proportional to ∑_Y, the necessary and sufficient conditions, under which (Y?μ)′W(Y?μ) with nonnegative definite W is generalized Wishart distributed, are obtained by using the higher moments of Y. This version of Cochran's theorem is general as the assumptions on ∑_Y=A?∑ with nonnegative definite A and ∑, P(Y?μ)=0, and P(Y≠μ)<1 have been relaxed. An example on two way balanced mixed models is given for illustration ot our main results.     

Phase-shifting common cycles and common trends

In this paper, we outline a framework for modelling and analysing economic fluctuations and dynamics. It is assumed that there may exist common trends and common cycles in the time series to be analysed It is further generalised that common cycles may have non-coincident, or phase-shifting attributes These attributes are examined via the Markov transition matrix in a VAR system, revealing the way in which the phase-shifting works with the reduced rank Markov transition matrix. The links with the structural common trend model are also presented.     

Sieve Estimation of Time-Varying Panel Data Models With Latent Structures

We propose a heterogeneous time-varying panel data model with a latent group structure that allows the coefficients to vary over both individuals and time. We assume that the coefficients change smoothly over time and form different unobserved groups. When treated as smooth functions of time, the individual functional coefficients are heterogeneous across groups but homogeneous within a group. We propose a penalized-sieve-estimation-based classifier-Lasso (C-Lasso) procedure to identify the individuals’ membership and to estimate the group-specific functional coefficients in a single step. The classification exhibits the desirable property of uniform consistency. The C-Lasso estimators and their post-Lasso versions achieve the oracle property so that the group-specific functional coefficients can be estimated as well as if the individuals’ membership were known. Several extensions are discussed. Simulations demonstrate excellent finite sample performance of the approach in both classification and estimation. We apply our method to study the heterogeneous trending behavior of GDP per capita across 91 countries for the period 1960–2012 and find four latent groups.     

Extreme Quantile Estimation for Autoregressive Models

ABSTRACT

A quantile autoregresive model is a useful extension of classical autoregresive models as it can capture the influences of conditioning variables on the location, scale, and shape of the response distribution. However, at the extreme tails, standard quantile autoregression estimator is often unstable due to data sparsity. In this article, assuming quantile autoregresive models, we develop a new estimator for extreme conditional quantiles of time series data based on extreme value theory. We build the connection between the second-order conditions for the autoregression coefficients and for the conditional quantile functions, and establish the asymptotic properties of the proposed estimator. The finite sample performance of the proposed method is illustrated through a simulation study and the analysis of U.S. retail gasoline price.     

Performance analysis of the retrial queues with finite number of sources and service interruptions

This paper aims at presenting an analytic approach for investigating a single-server retrial queue with finite population of customers where the server is subject to interruptions. A free source may generate a primary call to request service. If the server is free upon arrival, the call starts to be served and the service times are independent, generally distributed random variables. During the service time the source cannot generate a new primary call. After service the source moves into the free state and can generate a new primary call. There is no waiting space in front of the server, and a call who finds the server unavailable upon arrival joins an orbit of unsatisfied customers. The server is subject to interruptions during the service processes. When the server is interrupted, the call being served just before server interruption goes to the retrial orbit and will retry its luck after a random amount of time until it finds the server available. The recovery times of the interrupted server are assumed to be generally distributed. Our analysis extends previous work on this topic and includes the analysis of the arriving customer’s distribution, the busy period, and the waiting time process.     

国民时间资产和闲暇活动核算研究

一、问题的提出2 0世纪 60年代 ,发达国家经济已经达到了很高的水平。人们开始重视生活质量 ,探讨什么是真正的幸福等一系列问题。人们开始意识到仅用ＧＮＰ(ＧＤＰ)不能反映生活质量和幸福程度。例如 ,拥有很高的人均ＧＮＰ ,但是没有闲暇时间的生活 ,并不认为是高质量的生活。另外 ,2 0世纪中叶 ,伴随着妇女解放运动的开展 ,人们开始注意到家务劳动的价值 ,因此许多社会学家提出了建立社会指标的问题 ,也有许多经济学家提出家务劳动核算的问题。生活时间分配研究不仅可以从平均的角度反映国民个人的生活时间分配状况和生活方式 ,也可以从…     

2012年中国民族法学研究述评

2012年中国民族法学研究成果颇丰。其中,论文约有320余篇,比2011年增加了100余篇。这些研究在内容上有以下特点：一是内容较为全面,其中,民族习惯法、民族司法的研究比往年增多,民族政治权利成为年度重要话题;二是内容上的交叉研究增多;三是出现了一些综述性、反思性研究成果;四是关注了一些热点事件和话题;五是应用性研究成果较多。这些研究在方法上有以下特点：一是研究视角的多元化,协商民主成为年度新话题;二是注重实证研究;三是注重比较研究。在全面梳理的基础上,笔者根据研究内容所涉及的民族法学基本理论、民族权利保护、民族区域自治、民族法制建设、民族习惯法、民族法制史、民族司法等方面分别对其主要成果进行了介绍与评价,在辨别良莠、展示精华的同时,为不断繁荣中国民族法学提供可借鉴的年度综合性史料。