Robust importance sampling for some typical types of utility-based shortfall risk measures using exponential twisting and kernel density techniques

A robust algorithm for utility-based shortfall risk (UBSR) measures is developed by combining the kernel density estimation with importance sampling (IS) using exponential twisting techniques. The optimal bandwidth of the kernel density is obtained by minimizing the mean square error of the estimators. Variance is reduced by IS where exponential twisting is applied to determine the optimal IS distribution. Conditions for the best distribution parameters are derived based on the piecewise polynomial loss function and the exponential loss function. The proposed method not only solves the problem of sampling from the kernel density but also reduces the variance of the UBSR estimator.     

Bayesian misclassification and propensity score methods for clustered observational studies

Bayesian propensity score regression analysis with misclassified binary responses is proposed to analyse clustered observational data. This approach utilizes multilevel models and corrects for misclassification in the responses. Using the deviance information criterion (DIC), the performance of the approach is compared with approaches without correcting for misclassification, multilevel structure specification, or both in the study of the impact of female employment on the likelihood of physical violence. The smallest DIC confirms that our proposed model best fits the data. We conclude that female employment has an insignificant impact on the likelihood of physical spousal violence towards women. In addition, a simulation study confirms that the proposed approach performed best in terms of bias and coverage rate. Ignoring misclassification in response or multilevel structure of data would yield biased estimation of the exposure effect.     

Allocation strategies of standby redundancies in series/parallel system

This article deals with the topic of optimal allocation of two standby redundancies in a two-component series/parallel system. There are two original components C₁ and C₂ which can be used to construct a series/parallel system, and two spares R₁ (same as C₁) and R₂ (different from both C₁ and C₂) at hand with them being standby redundancies so as to enhance the reliability level of the system. The goal for an engineer is to seek after the optimal allocation policy in this framework. It is shown that, for the series structure, the engineer should allocate R₂ to C₁ and R₁ to C₂ provided that C₁ (or R₁) performs either the best or worst among all the units; otherwise, the allocation policy should be reversed. For the parallel structure, the optimal allocation strategy is just opposed to that of series case. We also provide some numerical examples for illustrating the theoretical results.     

Three strings of inequalities among six Bayes estimators

We discover three interesting strings of inequalities among six Bayes estimators, where for the parameter space (0, 1), (0, ∞), and ( ? ∞, ∞), each case has a string of inequalities. The three strings of inequalities only depend on the loss functions, and the inequalities are independent of the chosen models and the used priors provided the Bayes estimators exist. Therefore, they exist in a general setting which makes them quite interesting. Finally, the numerical simulations exemplify the two strings of inequalities defined on (0, 1) and (0, ∞), and that there does not exist a string of inequalities among the six smallest posterior expected losses.     

Semiparametric estimation of treatment effect with density ratio model

In this study we propose a unified semiparametric approach to estimate various indices of treatment effect under the density ratio model, which connects two density functions by an exponential tilt. For each index, we construct two estimating functions based on the model and apply the generalized method of moments to improve the estimates. The estimating functions are allowed to be non smooth with respect to parameters and hence make the proposed method more flexible. We establish the asymptotic properties of the proposed estimators and illustrate the application with several simulations and two real data sets.     

Asymptotic normality of the local linear estimation of the conditional density for functional time-series data

This article focuses on the conditional density of a scalar response variable given a random variable taking values in a semimetric space. The local linear estimators of the conditional density and its derivative are considered. It is assumed that the observations form a stationary α-mixing sequence. Under some regularity conditions, the joint asymptotic normality of the estimators of the conditional density and its derivative is established. The result confirms the prospect in Rachdi et al. (2014 Rachdi, M., A. Laksaci, J. Demongeot, A. Abdali, and F. Madani. 2014. Theoretical and practical aspects of the quadratic error in the local linear estimation of the conditional density for functional data. Computational Statistics and Data Analysis 73 :53–68.[Crossref], [Web of Science ®] , [Google Scholar]) and can be applied in time-series analysis to make predictions and build confidence intervals. The finite-sample behavior of the estimator is investigated by simulations as well.     

由感官之眼到心灵之眼——从不同审美纬度看现代艺术

形式和意义如同艺术史钟摆左右摇摆的两极,与之相应的抽象画和现成品艺术可谓形式的极端化和意义的具象化体现。在抽象画和现成品艺术面前,康德无功利的鉴赏判断主张与胡塞尔现象学悬隔态度下的审美直观规定了感官之眼的观看方式,后期胡塞尔及其之后的现象学家则通过对生活世界的回归,与社会学家布尔迪厄的趣味理论有不谋而合之处。在现代性席卷而来的当下,可从审美直观、意义阐释及符号化三个维度观看与传统艺术大不相同的现代艺术,发现感官之眼与心灵之眼在面向现代艺术时的博弈和融合。在此过程中,个人意识和集体意识、审美直观和意义阐释必然会此消彼长、交互作用,最终超越感官,到达心灵层面的审美体验。     

国有林生态效益补偿制度的缺失及其完善

长期以来,国有森林生态效益被无偿使用,森林经营者利益得不到保证,为保证国有林可持续发展经营,完善现行补偿制度刻不容缓。从法律管理的视角分析我国国有林生态效益补偿制度体系、补偿要素的内容、补偿的实施机制等方面的缺失,完善补偿制度应着眼于:国有林生态效益补偿法律制度立法目的与价值取向应该旨在协调国有林经营管护各方的利益,化解彼此间的利益冲突;维护社会公平,包括代内公平与代际公平;明确确定补偿范围,完善补偿要素;规范国有林生态效益补偿的行政管理体制,建立透明的国有林生态效益补偿信息公开制度、可持续的保障机制和完备的救济机制。     

The impact of health insurance cost-sharing method on healthcare utilisation in China

In current Chinese health insurance programmes, there are two types of cost-sharing methods: the time-of-service copayment policy and the reimbursement policy. In contrast to the copayment participants, reimbursement participants need to pay for all medical expenses in advance. We study the effect of the reimbursement policy on the utilisation of healthcare services in China. The theoretical analysis indicates that the medical consumption of low income households will be less than the optimal consumption level when enrolled in a reimbursement programme instead of a copayment programme. Empirically, using data from the China Health and Retirement Longitudinal Study (CHARLS), we find that the total inpatient expenditure of the reimbursement participants is 12.7% lower than that of copayment enrolees, and the reimbursement arrangement negatively impacts low-income and rural populations. Therefore, reimbursement participants, those who are financially constrained, are more likely to suffer the up-front payment burden and finally reduce their healthcare needs.