Lower Risk Bounds and Properties of Confidence Sets for Ill‐Posed Estimation Problems with Applications to Spectral Density and Persistence Estimation,Unit Roots,and Estimation of Long Memory Parameters

Important estimation problems in econometrics like estimating the value of a spectral density at frequency zero, which appears in the econometrics literature in the guises of heteroskedasticity and autocorrelation consistent variance estimation and long run variance estimation, are shown to be “ill‐posed” estimation problems. A prototypical result obtained in the paper is that the minimax risk for estimating the value of the spectral density at frequency zero is infinite regardless of sample size, and that confidence sets are close to being uninformative. In this result the maximum risk is over commonly used specifications for the set of feasible data generating processes. The consequences for inference on unit roots and cointegration are discussed. Similar results for persistence estimation and estimation of the long memory parameter are given. All these results are obtained as special cases of a more general theory developed for abstract estimation problems, which readily also allows for the treatment of other ill‐posed estimation problems such as, e.g., nonparametric regression or density estimation.     

小型光泵腔式NH3分子远红外激光器工作参数优化的实验研究

实验上采用金属网栅耦合的小型腔式NH3 分子远红外激光器 ,用TEA -CO2 激光器的 1 0R(8)和 9R(1 6)谱线作泵浦 ,获得了 2 81 μm和 90 .4μm的远红外激光 ,并对该激光器工作参数的优化进行了系统的实验研究     

基于MasterCAM的模具数控加工过程分析与应用

模具零件因其复杂的空间形面和形面特征而广泛采用数控加工方式。以常见的凹槽模具为例,基于MasterCAM对其数控加工过程进行了分析和参数设定。运用不同铣削方法完成了粗、精加工程序的编制与仿真,分析比较了典型的粗、精加工组合方式的加工质量和加工时间,确定了合理、高效的铣削方法。旨在探索一种优质、高效的数控加工方法,保汪加工精度和质量、缩短产品生产周期、降低加工成本。     

Q235钢静载拉伸磁记忆检测试验

为了研究磁记忆信号和应力之间的关系,采用磁记忆方法检测单向静载拉伸后Q235钢板表面磁场强度法向分 量Hp(y),并设计了更方便检测的拉伸试样。结果表明Q235试件断裂前磁场法向分量检测曲线为斜直线,具有唯一的 极性翻转点。同时还发现Q235材料处在弹性阶段时磁参数m值变化较慢,在塑性变形阶段时磁参数m值变化较快。     

效率参数不可观测下的SaaS云外包合约研究

客户企业在实施SaaS（软件即服务,Software as a Service）云外包时,面临因效率参数不可观测所引发的云服务提供商（Cloud Service Provider,CSP）道德风险问题。针对该问题,以激励机制设计方法为基础,以客户企业期望收益最大化为目标,在服务产出为公共信息,而效率参数信息为CSP私人信息下研究如何通过外包合约的设计诱使CSP显示出真实的信息,并付出最优的努力水平。研究表明,最优努力水平、服务报酬支付是效率参数的减函数;客户企业向CSP提供的最优合约可以用线性合约表示;在由固定服务报酬及收益共享构成的线性合约中,效率参数与固定服务报酬支付正相关,与收益共享系数负相关。     

Investigating dependence between frequency and severity via simple generalized linear models

Recently, a body of literature proposed new models relaxing a widely-used but controversial assumption of independence between claim frequency and severity in non-life insurance rate making. This paper critically reviews a generalized linear model approach, where a dependence between claim frequency and severity is introduced by treating frequency as a covariate in a regression model for severity. As an extension of this approach, we propose a dispersion model for severity. For this model, the information loss caused by using average severity rather than individual severity is examined in detail and the parameter estimators suffering from low efficiency are identified. We also provide analytical solutions for the aggregate sum to help rate making. We show that the simple functional form used in current research may not properly reflect the real underlying dependence structure. A real data analysis is given to explain our analytical findings.     

Liu estimator in partly linear regression models with correlated errors

This article is concerned with the parameter estimation in partly linear regression models when the errors are dependent. To overcome the multicollinearity problem, a generalized Liu estimator is proposed. The theoretical properties of the proposed estimator and its relationship with some existing methods designed for partly linear models are investigated. Finally, a hypothetical data is conducted to illustrate some of the theoretical results.     

On several estimates to the precision parameter of Dirichlet process prior

The article presents careful comparisons among several empirical Bayes estimates to the precision parameter of Dirichlet process prior, with the setup of univariate observations and multigroup data. Specifically, the data are equipped with a two-stage compound sampling model, where the prior is assumed as a Dirichlet process that follows within a Bayesian nonparametric framework. The precision parameter α measures the strength of the prior belief and kinds of estimates are generated on the basis of observations, including the naive estimate, two calibrated naive estimates, and two different types of maximum likelihood estimates stemming from distinct distributions. We explore some theoretical properties and provide explicitly detailed comparisons among these estimates, in the perspectives of bias, variance, and mean squared error. Besides, we further present the corresponding calculation algorithms and numerical simulations to illustrate our theoretical achievements.     

Testing equality of two beta binomial proportions in the presence of unequal extra-dispersion parameters

Data in the form of proportions with extra-dispersion (over/under) arise in many biomedical, epidemiological, and toxicological applications. In some situations, two samples of data in the form of proportions with extra-dispersion arise in which the problem is to test the equality of the proportions in the two groups with unspecified and possibly unequal extra-dispersion parameters. This problem is analogous to the traditional Behrens-Fisher problem in which two normal population means with possibly unequal variances are compared. To deal with this problem we develop eight tests and compare them in terms of empirical size and power, using a simulation study. Simulations show that a C(α) test based on extended quasi-likelihood estimates of the nuisance parameters holds nominal level most effectively (close to the nominal level) and it is at least as powerful as any other statistic that is not liberal. It has the simplest formula, is based on estimates of the nuisance parameters only under the null hypothesis, and is easiest to calculate. Also, it is robust in the sense that no distributional assumption is required to develop this statistic.