嵌入方式的生成及其在意图叙事中的功能——以元明清叙事文本为分析对象

序列的本质是行为者意图从生成到意图实现的过程。序列因行为者在叙事中的地位不同而分为主意图序列和次意图序列。嵌入是将次要人物意图序列插入主要人物意图序列的叙事方式。嵌入生成于主意图序列的内缺失和叙事者意图的外缺失及其合力。嵌入序列行为主体与主序列行为主体间存在着同意图与异意图、帮助者与反对者的不确定性关系,这两种关系的不确定导致故事的叙述方向不确定。中国古代叙事的嵌入方式有着独特的民族性,这种民族性源于中国古代特有的意象思维方式。     

长江下游文明化初期的人地关系--多学科交叉的实践与探索

以"全球变化研究"为标志的环境演变与人地关系研究,是国内外关注的课题.本文在全面收集考古资料基础上,采用考古地理学方法,利用文理交叉手段,对长江下游地区文明化初期人类发展与环境之间的互动关系进行了探讨.认为长江下游在整个中国历史文化进程乃至文明起源过程中,曾扮演过不同于其它地区的重要角色并有自身发展模式,为现代和未来的可持续发展提供了历史镜鉴.     

Poisson approximation and dna sequence matching

The Poisson distribution is commonly used to model the number of occurrences of independent rare events. However, many instances arise where dependence exists, for example, in counting the length of long head runs in coin tossing, or matches between two DNA sequences. The Chen-Stein method of Poisson approximation yields bounds on the error incurred when approximating the number of occurrences of possibly dependent events by a Poisson random variable of the same mean. In addition to the problems related to the motivating examples from molecular biology involving runs and matches, the method may be applied to questions as varied as calculating probabilities involving extremes of sequences of random variables and approximating the probability of general birthday coincidences.     

The Rise of Statistical Phylogenetics

This paper provides a review of the many applications of statistics within the field of phylogenetics, that is, the study of evolutionary history. The reader is assumed to be a statistician rather than a phylogeneticist, so some background is given on what phylogenetics is, along with a brief history of different approaches to phylogenetic inference. The latter half of the paper focuses on a series of open statistical problems in the field with the aim of encouraging more statisticians to engage with this fascinating area of research.     

Asymptotic Normality for Regression Function Estimate Under Truncation and α-Mixing Conditions

In this article we establish pointwise asymptotic normality of nonparametric kernel estimator of regression function for a left truncation model. It is assumed that the lifetime observations with multivariate covariates form a stationary α-mixing sequence. Also, the asymptotic normality of the estimation of the covariable's density is considered. As a by-product, we obtain a uniform weak convergence rate for the product-limit estimator of the lifetime and truncated distributions under dependence, which is interesting independently. Finite sample behavior of the estimator of the regression function is investigated as well.     

Consistency and Normality of M-Estimators in Partly Linear Models with Stochastic Adapted Errors

The robust M-estimators for the partly linear model under stochastic adapted errors are considered. It is shown that the M-estimator of parameter is asymptotically normal and the M-estimator of the nonparametric function achieves the optimal rate of convergence for nonparametric regression. Some known results are improved and generalized. Some simulations and a real data example are conducted to illustrate the proposed method.     

Change Detection in INAR(p) Processes Against Various Alternative Hypotheses

Change in the coefficients or the mean of the innovation of an INAR(p) process is a sign of disturbance that is important to detect. The proposed methods can test for change in any one of these quantities separately, or in any collection of them. They make both one-sided and two-sided tests possible, furthermore, they can be used to test against the “epidemic” alternative. The tests are based on a CUSUM process using CLS estimators of the parameters. Under the one-sided and two-sided alternatives, consistency of the tests is proved and the properties of the change-point estimator are also explored.     

Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing

Abstract. In the context of multivariate mean regression, we propose a new method to measure and estimate the inadequacy of a given parametric model. The measure is basically the missed fraction of variation after adjusting the best possible parametric model from a given family. The proposed approach is based on the minimum L ² ‐distance between the true but unknown regression curve and a given model. The estimation method is based on local polynomial averaging of residuals with a polynomial degree that increases with the dimension d of the covariate. For any d ≥ 1 and under some weak assumptions we give a Bahadur‐type representation of the estimator from which ‐consistency and asymptotic normality are derived for strongly mixing variables. We report the outcomes of a simulation study that aims at checking the finite sample properties of these techniques. We present the analysis of a dataset on ultrasonic calibration for illustration.     

地层倾角测井沉积构造与层序界面识别

采用相关对比法对关键井的地层倾角测井资料进行处理,结合地质构造图反映出的构造倾向,确定倾角资料长相关处理参数;结合岩芯照片对倾角资料进行微细处理,确定短相关处理参数。利用确定的长、短相关处理参数,对哈得逊地区的倾角测井资料进行处理,建立了东河砂岩储层典型的层理和微构造倾角解释模型;对中泥岩段开展了层序地层研究,根据长窗长倾角矢量图和累积倾角图,在中泥岩段识别出1个完整的三级层序、2个准层序组和5个准层序;利用短窗长处理的倾角矢量图,结合原始电导率曲线和倾角测井解释结果,进一步识别出中泥岩段有7个岩层组和16个岩层。