小说的生命叙事与人的生命建构

生命叙事把对人类肉身生存境况的关怀逐步推进到类似宗教境界的精神追求；它描述生命从物质到精神的孕育、产生、冲突、升腾的变化过程，是在对生命现实反思基础上的想像和升华。生命叙事的起点及归宿都是对蓬勃的生命状态的渴望和追求，它把叩问人类心灵的意义、建构理想的生命作为自己的神圣使命。     

Improving on truncated linear estimates of exponential and gamma scale parameters

We consider the problem of estimating the scale parameter of an exponential or a gamma distribution under squared error loss when the scale parameter θ is known to be greater than some fixed value θ₀. Natural estimators in this setting include truncated linear functions of the sufficient statistic. Such estimators are typically inadmissible, but explicit improvements seem difficult to find. Some are presented here. A particularly interesting finding is that estimators which are admissible in the untruncated problem which take values only in the interior of the truncated parameter space are found to be inadmissible for the truncated problem.     

预防职务犯罪的网络监督机制的构建

随着互联网技术和我国民主政治的发展,迫切要求研究如何构建预防职务犯罪的网络监督机制。这一机制是指以预防职务犯罪为目的,在一定基本原则指导下,参与网络监督的各种构成要素相互影响、相互作用的过程和方式。＂一定基本原则＂应包括实事求是、依法监督和反腐倡廉三个原则;＂参与网络监督的各种构成要素＂主要有网络监督管理者、网络监督主体、网络监督对象、网络监督内容、网络监督手段和方式等。＂相互影响、相互作用的过程和方式＂主要包括预防职务犯罪的网络监督程序的启动、网络监督信息的处理、网络监督处理结果的反馈等三方面内容。     

要科学制订我国科技部门统计机构发展对策

1985年全国科技统计普查以来,科技行政部门科技统计工作逐步形成了自上而下的完整体系。具体来讲,国家科技部通过地方各级科技行政管理层设立的对口机构,将统计制度贯彻下去,再将统计资料回收上来,运用本部门的管辖权对调查对象施行行政制约,保障统计过程的有效运转。目前,科技部科技统计工作初步形成了以科技部发展计划司牵头,以科技统计分析中心、科技统计信息中心和科技指标研究会等为支撑力量的工作体系。从1990年代中后期以来,各省市科技管理部门也成立了多种形式的科技统计机构,将直接调查的职能从政府部门中剥离出来,建立相对独立的…     

A likelihood ratio test for goodness‐of‐fit of recessive and dominant models for case–control studies

Testing goodness‐of‐fit of commonly used genetic models is of critical importance in many applications including association studies and testing for departure from Hardy–Weinberg equilibrium. Case–control design has become widely used in population genetics and genetic epidemiology, thus it is of interest to develop powerful goodness‐of‐fit tests for genetic models using case–control data. This paper develops a likelihood ratio test (LRT) for testing recessive and dominant models for case–control studies. The LRT statistic has a closed‐form formula with a simple $\chi^{2}(1)$ null asymptotic distribution, thus its implementation is easy even for genome‐wide association studies. Moreover, it has the same power and optimality as when the disease prevalence is known in the population. The Canadian Journal of Statistics 41: 341–352; 2013 © 2013 Statistical Society of Canada     

Parallel tempering for dynamic generalized linear models

ABSTRACT

Markov chain Monte Carlo (MCMC) methods can be used for statistical inference. The methods are time-consuming due to time-vary. To resolve these problems, parallel tempering (PT), as a parallel MCMC method, is tried, for dynamic generalized linear models (DGLMs), as well as the several optimal properties of our proposed method. In PT, two or more samples are drawn at the same time, and samples can exchange information with each other. We also present some simulations of the DGLMs in the case and provide two applications of Poisson-type DGLMs in financial research.     

A Bayesian Meta-Modeling Approach for Gaussian Stochastic Process Models Using a Non Informative Prior

In this article, an efficient Bayesian meta-modeling approach is proposed for Gaussian stochastic process models in computer experiments. Different prior densities and particularly, a non informative hyper prior have been employed on the parameters involved in the correlation matrix. And the estimation of related parameters is obtained by the expectation-maximization algorithm. Compared with the recent work of Li and Sudjianto (2005 Li , R. , Sudjianto , A. ( 2005 ). Analysis of computer experiments using penalized likelihood in Kriging models . Technometrics 47 : 111 – 120 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), the proposed approach is not only of higher prediction accuracy but also of lower computational cost, due to the utilization of the non informative prior and the absence of tuning parameters. Experimental results demonstrate that our approach yields state-of-the-art performance.     

Nonparametric Trend Estimation for Periodic Autoregressive Time Series

A periodically stationary time series has seasonal variances. A local linear trend estimation is proposed to accommodate unequal variances. A comparison of this proposed estimator with the estimator commonly used for a stationary time series is provided. The optimal bandwidth selection for this new trend estimator is discussed.     

Inference for Time Series Regression Models With Weakly Dependent and Heteroscedastic Errors

Motivated by the need to assess the significance of the trend in some macroeconomic series, this article considers inference of a parameter in parametric trend functions when the errors exhibit certain degrees of nonstationarity with changing unconditional variances. We adopt the recently developed self-normalized approach to avoid the difficulty involved in the estimation of the asymptotic variance of the ordinary least-square estimator. The limiting distribution of the self-normalized quantity is nonpivotal but can be consistently approximated by using the wild bootstrap, which is not consistent in general without studentization. Numerical simulation demonstrates favorable coverage properties of the proposed method in comparison with alternative ones. The U.S. nominal wages series is analyzed to illustrate the finite sample performance. Some technical details are included in the online supplemental material.