Optimal Information Processing and Bayes's Theorem

In this article statistical inference is viewed as information processing involving input information and output information. After introducing information measures for the input and output information, an information criterion functional is formulated and optimized to obtain an optimal information processing rule (IPR). For the particular information measures and criterion functional adopted, it is shown that Bayes's theorem is the optimal IPR. This optimal IPR is shown to be 100% efficient in the sense that its use leads to the output information being exactly equal to the given input information. Also, the analysis links Bayes's theorem to maximum-entropy considerations.     

Controlled Direct and Mediated Effects: Definition,Identification and Bounds

Abstract. Results are given which provide bounds for controlled direct effects when nounmeasured confounding assumptions required for the identification of these effects do not hold. Previous results concerning bounds for controlled direct effects rely on monotonicity relationships between the treatment, mediator and the outcome themselves; the results presented in this article instead assume that monotonicity relationships hold between the unmeasured confounding variable or variables and the treatment, mediator and outcome. Whereas prior results give bounds that contain the null hypothesis of no direct effect, the results presented here will in many instances yield bounds that do not contain the null hypothesis of no direct effect. For contexts in which a set of variables intercepts all paths between a treatment and an outcome, it is possible to provide a definition for a controlled mediated effect. We discuss the identification of these controlled mediated effects; the bounds for controlled direct effects are applicable also to controlled mediated effects. An example is given to illustrate how the results in the article can be used to draw inferences about direct and mediated effects in the presence of unmeasured confounding variables.     

Bootstrap confidence bands for the CDF using ranked-set sampling

In ranked-set sampling (RSS), a stratification by ranks is used to obtain a sample that tends to be more informative than a simple random sample of the same size. Previous work has shown that if the rankings are perfect, then one can use RSS to obtain Kolmogorov–Smirnov type confidence bands for the CDF that are narrower than those obtained under simple random sampling. Here we develop Kolmogorov–Smirnov type confidence bands that work well whether the rankings are perfect or not. These confidence bands are obtained by using a smoothed bootstrap procedure that takes advantage of special features of RSS. We show through a simulation study that the coverage probabilities are close to nominal even for samples with just two or three observations. A new algorithm allows us to avoid the bootstrap simulation step when sample sizes are relatively small.     

认知语境的构建

本文在关联理论的框架下讨论发话人怎袢通过语言和非语言手段制约受话人的认知语境以及受话人如何在认知环境中选择并延伸认知语境.     

浅谈语境与交际

本文从语用学角度出发探讨了语境与交际的关系.重点论述了人们在交际过程中,在交际模式的指导下如何利用语境,寻找到最佳的关联,推理出说话者的真正意图,具体分析了语境在交际中所起的重大作用.     

模糊取式推理的R0方法

用R0蕴涵算子描述了模糊命题“若A则B”,并通过一个例子给出了运用模糊取式推理的R0方法进行推理的具体操作过程．结果表明,运用该模糊推理得到的结论是与人们的思想相吻合的．     

Grice语用学模式批判

在话语理解中 ,通过解码获得语义 ,通过推理得出说话人意图。在语用学的发展过程中 ,话语理解的重心逐渐转移到推理过程 ,Grice的推理模式就是这种发展的代表 ,认为交际中人们遵守着合作原则以及相关准则 ,违背某些准则是为了表达暗含意义 ,需要推理求得理解。然而 ,Grice过分强调暗含意义 ,而且合作原则及有关准则来源不清 ,严重地削弱了Grice推理模式的解释力。     

统计学发展过程中四次重要的争论及其影响

统计学发展过程中出现过几次重大的争论,这些争论在本质上可以说是一脉相承的。"政治算术"与"国势学"的争论,明确了统计学的学科性质;"描述统计学"与"推断统计学"的争论,构筑了统计学的完整体系;"经典统计学"与"贝叶斯统计学"的争论,带来了统计哲学观的新变化;信念统计学与经典统计学、贝叶斯统计学的争论,使统计推断科学化问题的研究日趋深入。正是通过这些争论完善了现代统计学的思想和方法体系。     

Marginal Regression of Gaps Between Recurrent Events

Recurrent event data typically exhibit the phenomenon of intra-individual correlation, owing to not only observed covariates but also random effects. In many applications, the population may be reasonably postulated as a heterogeneous mixture of individual renewal processes, and the inference of interest is the effect of individual-level covariates. In this article, we suggest and investigate a marginal proportional hazards model for gaps between recurrent events. A connection is established between observed gap times and clustered survival data with informative cluster size. We subsequently construct a novel and general inference procedure for the latter, based on a functional formulation of standard Cox regression. Large-sample theory is established for the proposed estimators. Numerical studies demonstrate that the procedure performs well with practical sample sizes. Application to the well-known bladder tumor data is given as an illustration.     

时间贝叶斯网络及其概率推理

针对贝叶斯网络应用中出现的循环和动态问题,研究贝叶斯网络的时间扩展.给出了时间贝叶斯网络的定义;探讨了时间贝叶斯网络中环的存在合理性判断问题;给出了时间贝叶斯网络的概率推理算法,应用示例说明了方法的可行性.