一类广义(2+1)维非自治长短波方程的整体光滑解的存在唯一性

利用先验估计和Galerkin方法,研究了非线性广义耗散(2+1)维非自治长短波方程在H4per(Ω)×H3per(Ω)上光滑解的整体存在唯一性.     

中国上市公司监事会规模和构成的影响因素

理论分析表明,监事会规模及构成内生于公司风险。文章构建联立方程模型实证考察了监事会规模和构成的影响因素,在控制了内生性和制度因素影响后发现：公司经营范围、监督收益对监事会规模和职工监事比例有显著正向影响;监督成本、管理者权力对监事会规模和职工监事比例有显著负向影响。还发现：在控制了监事会规模和构成的影响因素后,监事会规模和职工监事比例与公司风险并没有统计意义上的相关性,表明监事会未能有效发挥降低公司风险的治理作用。因此,加强监事会能力建设,推进公司治理体系和治理能力现代化,仍将是中国公司治理改革努力的方向。     

Smooth-Threshold GEE Variable Selection in High-Dimensional Partially Linear Models with Longitudinal Data

We consider the problem of variable selection in high-dimensional partially linear models with longitudinal data. A variable selection procedure is proposed based on the smooth-threshold generalized estimating equation (SGEE). The proposed procedure automatically eliminates inactive predictors by setting the corresponding parameters to be zero, and simultaneously estimates the nonzero regression coefficients by solving the SGEE. We establish the asymptotic properties in a high-dimensional framework where the number of covariates p_n increases as the number of clusters n increases. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed variable selection procedure.     

一类椭圆型方程广义解的Holder连续性

本文证明了下面方程的广义解ｕ∈（ａ，Ｇ）∩Ｌ∞（Ｇ）在Ｇ的Ｈｏｌｄｅｒ连续性。关于Ａ和Ｂ，要求满足如下的结构不等式。     

Macroeconomic asymmetry in the Eurozone before and after the Global Financial Crisis: An appraisal of the role of the ECB

The launch of the euro in 1999 was assumed to enhance macroeconomic convergence among EMU economies. We test this hypothesis from a comparative perspective, by calculating different indices to measure the degree of macroeconomic dispersion within the Eurozone, the UK and the USA (1999–2019). We use common factor models to produce a single index for each monetary area out of different measures of dispersion. These indices can be used to inform on the degree of optimality of a monetary area. Our results show that macroeconomic dispersion in the Eurozone increased notably even before 2007 and it took significantly longer to return to pre-crisis levels, as compared to the UK and the USA. The paper shows the critical role played by the ECB’s asset purchases programmes in reducing macroeconomic divergences among EMU member states since 2015.     

关于一类发展方程Hamilton正则形式的实现

本文首先利用前人的重要结论巧妙地给出了一类发展方程Hamilton正则形式规范化的实现步骤;其次,对特殊三阶Hamilton算子确定的发展方程化为正则形式做了进一步的推广;最后,通过3个算例验证了本文方法的可行性。     

A Characterization of the Normal Family of Distributions Based on the Bias of the Maximum Likelihood Estimator

This paper characterizes the family of Normal distributions within the class of exponential families of distributions, via the structure of the bias of the maximum likelihood estimator Θ _n of the canonical parameter Θ . More specifically, when E _θ ( Θ n ) – Θ = (1/ n ) Q ( Θ ) + o (1/ n ), the equality Q ( Θ ) = 0 proves to be a property of the Normal distribution only. The same conclusion is obtained for the one-dimensional case bt assuming that Q ( Θ ) is a polynomial of Θ .     

Saddlepoint-Based Bootstrap Inference for Quadratic Estimating Equations

Abstract.  We propose an easy to implement method for making small sample parametric inference about the root of an estimating equation expressible as a quadratic form in normal random variables. It is based on saddlepoint approximations to the distribution of the estimating equation whose unique root is a parameter's maximum likelihood estimator (MLE), while substituting conditional MLEs for the remaining (nuisance) parameters. Monotoncity of the estimating equation in its parameter argument enables us to relate these approximations to those for the estimator of interest. The proposed method is equivalent to a parametric bootstrap percentile approach where Monte Carlo simulation is replaced by saddlepoint approximation. It finds applications in many areas of statistics including, nonlinear regression, time series analysis, inference on ratios of regression parameters in linear models and calibration. We demonstrate the method in the context of some classical examples from nonlinear regression models and ratios of regression parameter problems. Simulation results for these show that the proposed method, apart from being generally easier to implement, yields confidence intervals with lengths and coverage probabilities that compare favourably with those obtained from several competing methods proposed in the literature over the past half-century.     

Asymptotic Analysis of the Sieve Estimator for a Class of Parabolic SPDEs

In this paper we consider the problem of estimating a coefficient of a strongly elliptic partial differential operator in stochastic parabolic equations. The coefficient is a bounded function of time. We compute the maximum likelihood estimate of the function on an approximating space (sieve) using a finite number of the spatial Fourier coefficients of the solution and establish conditions that guarantee consistency and asymptotic normality of the resulting estimate as the number of the coefficients increases. The equation is assumed diagonalizable in the sense that all the operators have a common system of eigenfunctions.