Analysis of Competing Risks by Using Bayesian Smoothing

We consider the competing risks set-up. In many practical situations, the conditional probability of the cause of failure given the failure time is of direct interest. We propose to model the competing risks by the overall hazard rate and the conditional probabilities rather than the cause-specific hazards. We adopt a Bayesian smoothing approach for both quantities of interest. Illustrations are given at the end.     

Bayesian prediction of waiting times in stochastic models

The authors show how saddlepoint techniques lead to highly accurate approximations for Bayesian predictive densities and cumulative distribution functions in stochastic model settings where the prior is tractable, but not necessarily the likelihood or the predictand distribution. They consider more specifically models involving predictions associated with waiting times for semi‐Markov processes whose distributions are indexed by an unknown parameter θ. Bayesian prediction for such processes when they are not stationary is also addressed and the inverse‐Gaussian based saddlepoint approximation of Wood, Booth & Butler (1993) is shown to accurately deal with the nonstationarity whereas the normal‐based Lugannani & Rice (1980) approximation cannot, Their methods are illustrated by predicting various waiting times associated with M/M/q and M/G/1 queues. They also discuss modifications to the matrix renewal theory needed for computing the moment generating functions that are used in the saddlepoint methods.     

On optimal testing for the equality of equicorrelation: An example of loss in power

Sen Gupta (1988) considered a locally most powerful (LMP) test for testing nonzero values of the equicorrelation coefficient of a standard symmetric multivariate normal distribution. This paper constructs analogous tests for the symmetric multivariate normal distribution. It shows that the new test is uniformly most powerful invariant even in the presence of a nuisance parameter, σ². Further applications of LMP invariant tests to several equicorrelated populations have been considered and an extension to panel data modeling has been suggested.     

Asymptotic Bias in Parameter Estimation of AR-Processes Using Recursive Least Squares with Exponential Forgetting

The recursive least squares technique is often extended with exponential forgetting as a tool for parameter estimation in time-varying systems. The distribution of the resulting parameter estimates is, however, unknown when the forgetting factor is less than one. In this paper an approximative expression for bias of the recursively obtained parameter estimates in a time-invariant AR( n_a ) process with arbitrary noise is given, showing that the bias is non-zero and giving bounds on the approximation errors. Simulations confirm the approximation expressions.     

光谱法测量等离子体离子温度和再循环粒子流速

利用多道光学分析仪（OSMA）测量HT-6M托卡马克限制器前Hα线形分布,通过高斯拟合由多普勒展宽和多普勒频移分别得出等离子体离子温度和再循环粒子流速。     

广东普通工科高等教育的办学效益分析研究

对广东普通工科高等教育的办学效益问题,从结构布局效益、层次与规模效益进行了讨论,提出了提高办学效益的基本对策。     

农户土地流转有助于农户群体“提低扩中”吗?

提高中低收入农户群体的收入水平是缩小居民收入差距、实现共同富裕的关键任务。利用CFPS 2018数据,使用基于RIF的ITE模型等计量方法进行分析研究发现：(1)土地流转的增收效应具有非对称性,转出土地的中低收入农户能显著增收,但转入土地的中低收入农户增收不明显;(2)东部和西部地区转出土地的中低收入农户收入增长显著;(3)土地流转(尤其是转出)有助于缩小农户间收入差距、优化农户群体的收入分配结构。实证结果稳健地说明农户土地流转对实现农户群体“提低扩中”目标具有积极意义,在此基础上提出在西部和东中部欠发达农村地区,鼓励和支持中低收入农户流转土地,以增加其兼业和非农收入等政策建议。     

长江流域城市人口分布及空间相关性研究

本文选取长江流域104个城市人口样本作为研究对象,采用人口分布的结构指数和空间自相关分析方法,以及借用GIS技术来研究长江流域城市人口分布的空间动态特征和城市人口之间的功能联系。结果表明,长江流域城市人口空间结构呈均衡发展态势;人口密度分布呈现趋同趋势;城市人口与邻近城市人口之间的空间正相关要多于空间负相关;长江流域城市人口之间的空间关联性被分为八种类型。     

不同信息透明度对分销系统及各成员的影响

考虑由一个供应商和多个零售商组成的分销系统。研究高、中、低三种不同信息透明度模式下系统的最优补货及分配策略以及相应的系统和各个零售商的期望成本。证明无论从系统的角度还是从零售商的角度,并非信息透明度越高,期望成本越低。从整个系统的角度来讲,虽然系统的期望成本总在高信息透明度模式下取得最低,但是,中低两种信息透明度模式谁取得第二低的系统期望成本取决于系统内各节点之间的距离以及零售商所面对客户需求的性质。从零售商的角度,高信息透明度并不能降低零售商的期望成本。零售商是否可以从较高的信息透明度水平中获益则取决于零售商在送货路线上所处的位置,系统内各节点之间的距离,以及零售商所面对客户需求的性质。