Noninformative priors for the between-group variance in the unbalanced one-way random effects model with heterogeneous error variances

For the unbalanced one-way random effects model with heterogeneous error variances, we propose the non-informative priors for the between-group variance and develop the first- and second-order matching priors. It turns out that the second-order matching priors do not exist and the reference prior and Jeffreys prior do not satisfy a first-order matching criterion. We also show that the first-order matching prior meets the frequentist target coverage probabilities much better than the Jeffreys prior and reference prior through simulation study, and the Bayesian credible intervals based on the matching prior and reference prior give shorter intervals than the existing confidence intervals by examples.     

Uniform consistency rate of kNN regression estimation for functional time series data

In this paper, we investigate the k-nearest neighbours (kNN) estimation of nonparametric regression model for strong mixing functional time series data. More precisely, we establish the uniform almost complete convergence rate of the kNN estimator under some mild conditions. Furthermore, a simulation study and an empirical application to the real data analysis of sea surface temperature (SST) are carried out to illustrate the finite sample performances and the usefulness of the kNN approach.     

生命的困境与心灵的自由——庄子的人生哲学

庄子人生哲学的根本宗旨是实现对构成生命困境的必然性因素 (“命”)的超越 ,达到个体生命心灵的绝对自由 (“逍遥”)。庄子将人生所面临的生死、时势、情欲等困境概括为一种必然性范畴———“命”。而作为“逍遥哲学”的开创者 ,庄子找到了三种超越生命困境、实现心灵自由的途径 :安命、齐物、体道     

村委会职能立法的基本情况及存在的问题——以立法条文为分析对象

当前为村委会设置职能的法律既有国家统一立法也有地方立法。通过分析发现：统一立法所反映的村委会性质有所差异,在不同立法中不能保持恒定;指导及协助关系不仅存在于乡、镇政府与村委会之间,还存在于村委会与众多主体之间;立法中的某些职能设置没有充分考虑村委会的适格性问题,从而使村委会无法胜任。各省《村组法》实施办法中的职能规定,主要是大量重复《村组法》的内容,虽然在实施方式、方法以及步骤上起了一些具体化的作用,但并不普遍,尚未实现统一立法的“本土化”。在使村委会的职能具体化以及可操作化这一问题上,其他地方性法规以及部门规章做得比《村组法》实施办法成功得多,但它们在这一过程中增加了村委会的工作量,同时也强化了行政机构对村委会的控制。     

分贷统还合同的法律性质与违约风险化解

分贷统还合同为政府通过合约统一贴息实现了扶贫资金的公司化运作,有效地发挥财政扶贫资金的整体效益,但也产生了合同法律性质认定争议大、合同履行易受政策变化影响;户贷企用导致贷款用途和资金安全存在风险,公司分红还款系统性违约等弊端,如公司经营不善,贷款亏空,一旦出现系统性违约,不仅影响农村社会稳定和政府公信力,司法机关亦将面临纠纷批量涌入的现实问题。为趋利避害,分贷统还合同有必要在综合衡量扶贫目的、公司盈利及扶贫责任和银行资金安全的基础上,调整户贷企用政策,甄别债权类型,考虑违约的具体情势,从实操层面化解分贷统还合同违约风险。     

政府问责视野中的国家精品课程复核研究

运用新公共服务理论和行政优益权理论分析,国家精品课程建设实质上是教育部为向公众提供优质的高等教育服务、确保优质资源的开放共享,而与申请国家精品课程的高校签订的行政契约,政府作为公共利益的集中代表,有权对国家精品课程建设给予监督并实施复核。     

Statistical modeling for Bayesian extrapolation of adult clinical trial information in pediatric drug evaluation

Children represent a large underserved population of “therapeutic orphans,” as an estimated 80% of children are treated off‐label. However, pediatric drug development often faces substantial challenges, including economic, logistical, technical, and ethical barriers, among others. Among many efforts trying to remove these barriers, increased recent attention has been paid to extrapolation; that is, the leveraging of available data from adults or older age groups to draw conclusions for the pediatric population. The Bayesian statistical paradigm is natural in this setting, as it permits the combining (or “borrowing”) of information across disparate sources, such as the adult and pediatric data. In this paper, authored by the pediatric subteam of the Drug Information Association Bayesian Scientific Working Group and Adaptive Design Working Group, we develop, illustrate, and provide suggestions on Bayesian statistical methods that could be used to design improved pediatric development programs that use all available information in the most efficient manner. A variety of relevant Bayesian approaches are described, several of which are illustrated through 2 case studies: extrapolating adult efficacy data to expand the labeling for Remicade to include pediatric ulcerative colitis and extrapolating adult exposure‐response information for antiepileptic drugs to pediatrics.     

A powerful and efficient algorithm for breaking the links between aliased effects in asymmetric designs

Fractional factorial (FF) designs are no doubt the most widely used designs in experimental investigations due to their efficient use of experimental runs. One price we pay for using FF designs is, clearly, our inability to obtain estimates of some important effects (main effects or second order interactions) that are separate from estimates of other effects (usually higher order interactions). When the estimate of an effect also includes the influence of one or more other effects the effects are said to be aliased. Folding over an FF design is a method for breaking the links between aliased effects in a design. The question is, how do we define the foldover structure for asymmetric FF designs, whether regular or nonregular? How do we choose the optimal foldover plan? How do we use optimal foldover plans to construct combined designs which have better capability of estimating lower order effects? The main objective of the present paper is to provide answers to these questions. Using the new results in this paper as benchmarks, we can implement a powerful and efficient algorithm for finding optimal foldover plans which can be used to break links between aliased effects.     

A new Bayesian wavelet thresholding estimator of nonparametric regression

The methods of estimation of nonparametric regression function are quite common in statistical application. In this paper, the new Bayesian wavelet thresholding estimation is considered. The new mixture prior distributions for the estimation of nonparametric regression function by applying wavelet transformation are investigated. The reversible jump algorithm to obtain the appropriate prior distributions and value of thresholding is used. The performance of the proposed estimator is assessed with simulated data from well-known test functions by comparing the convergence rate of the proposed estimator with respect to another by evaluating the average mean square error and standard deviations. Finally by applying the developed method, density function of galaxy data is estimated.     

Flexible objective Bayesian linear regression with applications in survival analysis

We study objective Bayesian inference for linear regression models with residual errors distributed according to the class of two-piece scale mixtures of normal distributions. These models allow for capturing departures from the usual assumption of normality of the errors in terms of heavy tails, asymmetry, and certain types of heteroscedasticity. We propose a general non-informative, scale-invariant, prior structure and provide sufficient conditions for the propriety of the posterior distribution of the model parameters, which cover cases when the response variables are censored. These results allow us to apply the proposed models in the context of survival analysis. This paper represents an extension to the Bayesian framework of the models proposed in [16]. We present a simulation study that shows good frequentist properties of the posterior credible intervals as well as point estimators associated to the proposed priors. We illustrate the performance of these models with real data in the context of survival analysis of cancer patients.