基于星历拟合的GPS广播星历参数评估分析

为了更好地利用广播星历参数进行导航电文参数的优化设计,在拟合GPS广播星历参数的基础上,通过减少其中不同的调和项系数,分别对预报星历进行拟合计算分析,以对不同的GPS广播星历参数进行质量评估．结果表明,去掉GPS广播星历15参数中的Cic。Cic2个参数后用余下的13参数仍能满足普通用户的导航定位较高精度的要求．     

利用迭代滤波改进乘积高阶模糊函数

乘积高阶模糊函数(PHAF)是因分析mc-PPS而提出来的,但它抑制交叉项的能力有限,难以实现mc-PPS估计。该文提出了逐次滤除最强PHAF峰对应的分量来减少交叉项的迭代滤波方法,改进后的PHAF具有较好的鲁棒性:减少了估计盲区,并且具有更好的估计精度,降低了信噪比门限,而且能估计低阶相位系数,这些性能由多个mc-PPS仿真例子所验证。     

基于免疫原理的控制器参数整定方法

基于免疫原理,建立了一个基于免疫机制进行控制器参数整定的数学模型。给出了参数整定问题中抗原、抗体和亲和力的定义,对基于免疫原理的控制器参数整定过程进行了详细的描述。最后以PID的参数整定为例,控制一个高阶系统,大延迟系统和非最小相位系统。并与Z-N,MOMI等算法的整定结果进行了对比实验,结果表明该方法对控制器的参数整定是有效的。     

我国农村居民消费结构的稳定性分析

利用邹氏稳定性检验方法对我国农村居民消费行为的稳定性进行分析,发现从1990年以来农村居民的消费结构发生了质的变化。根据这种分析,应用变参数模型分析农村居民消费和收入的关系,得出农村居民消费对农村居民收入存在着显著的影响关系的结论,提出保持农民收入持续增长,促进消费提高,进而促进农民收入提高的建议。     

A smoothed Q‐learning algorithm for estimating optimal dynamic treatment regimes

In this paper, we propose a smoothed Q‐learning algorithm for estimating optimal dynamic treatment regimes. In contrast to the Q‐learning algorithm in which nonregular inference is involved, we show that, under assumptions adopted in this paper, the proposed smoothed Q‐learning estimator is asymptotically normally distributed even when the Q‐learning estimator is not and its asymptotic variance can be consistently estimated. As a result, inference based on the smoothed Q‐learning estimator is standard. We derive the optimal smoothing parameter and propose a data‐driven method for estimating it. The finite sample properties of the smoothed Q‐learning estimator are studied and compared with several existing estimators including the Q‐learning estimator via an extensive simulation study. We illustrate the new method by analyzing data from the Clinical Antipsychotic Trials of Intervention Effectiveness–Alzheimer's Disease (CATIE‐AD) study.     

Fitting the generalized Pareto distribution to data based on transformations of order statistics

Generalized Pareto distribution (GPD) has been widely used to model exceedances over thresholds. In this article we propose a new method called weighted nonlinear least squares (WNLS) to estimate the parameters of the GPD. The WNLS estimators always exist and are simple to compute. Some asymptotic results of the proposed method are provided. The simulation results indicate that the proposed method performs well compared to existing methods in terms of mean squared error and bias. Its advantages are further illustrated through the analysis of two real data sets.     

Estimation of time-varying coefficient dynamic panel data models

In this paper, we consider dynamic panel data models where the autoregressive parameter changes over time. We propose the GMM and ML estimators for this model. We conduct Monte Carlo simulation to compare the performance of these two estimators. The simulation results show that the ML estimator outperforms the GMM estimator.     

The Almon two parameter estimator for the distributed lag models

The two parameter estimator proposed by Özkale and Kaç?ranlar [The restricted and unrestricted two parameter estimators. Comm Statist Theory Methods. 2007;36(15):2707–2725] is a general estimator which includes the ordinary least squares, the ridge and the Liu estimators as special cases. In the present paper we introduce Almon two parameter estimator based on the two parameter estimation procedure to deal with the problem of multicollinearity for the distiributed lag models. This estimator outperforms the Almon estimator according to the matrix mean square error criterion. Moreover, a numerical example and a Monte Carlo simulation experiment are presented by using different estimators of the biasing parameters.     

论提升中国证券市场的结构

经过十多年的发展,中国的证券市场已成为市场经济体系中不可或缺的一部分。但由于历史和制度的原因,目前中国证券市场的结构还存在一些不足,如股票和债券市场的发展失衡、主体结构不合理、中介机构不完善等。这些问题的存在严重制约了证券市场的健康发展。对此,本文提出优化和提升中国证券市场结构的策略和措施。