基于概率结构的纽康姆难题消解方案

纽康姆难题制造的选择困境极大地挑战了经典决策原则。为了维护贝叶斯决策理论的规范性,有人怀疑甚至否定其存在的合理性。借助贝叶斯网络和概率理论,可以直观地展示决策者的行动和预言家的预测之间的因果关系,并揭示出选择困境的实质:纽康姆难题中存在两种不相容的概率结构。因此,它的一个恰当消解方案就是:用清晰的语言来描述纽康姆难题的选择情境,使其仅具有单一概率结构。     

Model Similarity and Rank-Order Based Classification of Bayesian Networks

Suppose that we rank-order the conditional probabilities for a group of subjects that are provided from a Bayesian network (BN) model of binary variables. The conditional probability is the probability that a subject has a certain attribute given an outcome of some other variables and the classification is based on the rank-order. Under the condition that the class sizes are equal across the class levels and that all the variables in the model are positively associated with each other, we compared the classification results between models of binary variables which share the same model structure. In the comparison, we used a BN model, called a similar BN model, which was constructed under some rule based on a set of BN models satisfying certain conditions. Simulation results indicate that the agreement level of the classification between a set of BN models and their corresponding similar BN model is considerably high with the exact agreement for about half of the subjects or more and the agreement up to one-class-level difference for about 90% or more.     

Classification Based on Depth Transvariations

Suppose y, a d-dimensional (d ≥ 1) vector, is drawn from a mixture of k (k ≥ 2) populations, given by ∏₁, ∏₂,…,∏ _k . We wish to identify the population that is the most likely source of the point y. To solve this classification problem many classification rules have been proposed in the literature. In this study, a new nonparametric classifier based on the transvariation probabilities of data depth is proposed. We compare the performance of the newly proposed nonparametric classifier with classical and maximum depth classifiers using some benchmark and simulated data sets. The authors thank the editor and referees for comments that led to an improvement of this paper. This work is partially supported by the National Science Foundation under Grant No. DMS-0604726. Published online xx, xx, xxxx.     

从肖克莱发明晶体管看创造性思维过程

诺贝尔物理学奖获得者肖克莱一生发明了多种晶体管,其在贝尔电话实验室期间发明的PN结型晶体管和结型场效应晶体管尤为著名.本文对这两种晶体管构想的形成与实现过程进行了较为详细的考察,并在此基础上对创造性思维过程的阶段划分问题进行了初步探讨.     

三角测量模式对知识客观真理性的辩护

现代知识论研究将信念的辩护作为知识辩护问题的切入点。本文在当代知识分析的背景下,从两个主要的信念辩护模式及其不足的讨论中引出由戴维森提出的三角测量模式,通过揭示三角测量在给出信念的客观经验内容和客观真理性概念、把握信念-真理的主客观对比方面的独特作用,展示其具有克服以往信念辩护模式的缺陷和反驳怀疑论的能力,从而能够作为信念客观真理性辩护的新模式。     

概率哲学思想的几次进化

概率哲学思想的发展,不仅受到社会、经济和生产力发展的影响,且同自然科学和社会科学相联系,连同本身的内在矛盾相互制约、彼此推动,促使其从对立矛盾发展到相对和谐统一,而形成了概率论的基本内容、基本形式以及方法论上的重大变革。     

奥斯特罗格拉茨基的概率思想探赜

奥斯特罗格拉茨基是圣彼得堡概率学派的杰出代表,其对相关实际问题的应用研究推动了概率论在俄罗斯的传播和发展。他坚持认为概率论是数学分析最重要的应用分支之一:为天文学提供了大量基本数学观察方法,可确定比数学观察误差影响还要小的随机事件原因等,其社会服务功能刺激了诸如保险业等社会福利机构的产生和发展,进而促进了自然科学的相关理论发展。由于深受拉普拉斯概率思想之影响,奥斯特罗格拉茨基虽然把概率论看作研究随机现象规律的有力工具,但经常犯一些哲学观和方法论错误。     

Measuring the Reliability of Diagnostic Classification Model Examinee Estimates

Over the past decade, diagnostic classification models (DCMs) have become an active area of psychometric research. Despite their use, the reliability of examinee estimates in DCM applications has seldom been reported. In this paper, a reliability measure for the categorical latent variables of DCMs is defined. Using theory-and simulation-based results, we show how DCMs uniformly provide greater examinee estimate reliability than IRT models for tests of the same length, a result that is a consequence of the smaller range of latent variable values examinee estimates can take in DCMs. We demonstrate this result by comparing DCM and IRT reliability for a series of models estimated with data from an end-of-grade test, culminating with a discussion of how DCMs can be used to change the character of large scale testing, either by shortening tests that measure examinees unidimensionally or by providing more reliable multidimensional measurement for tests of the same length.     

试析凯恩斯概率逻辑思想产生的历史条

凯恩斯的概率逻辑在归纳逻辑史上具有开创性的意义．它使归纳逻辑向形式化的方向前进了一大步。凯恩斯的概率逻辑思想集中体现在1921年出版的《论概率》一书中, 《论概率》是概牢逻辑史上的第一部较为系统的著作,是归纳理论发展的一个...     

基于A-U模型的企业R&D过程知识分布及其自组织倾向

本文以A-U模型的三个阶段的划分为基础,以知识论和知识管理的相关研究成果为理论方法,分析了企业R&D过程中隐形知识、显形知识的分布、构成、转化及自适应、自组织倾向,认为在企业R&D过程中知识类型经历了一个可编码化和显形性逐步上升和提高的过程.     

科学史的可能性研究

由对科学史的主体和对象的阐释入手,探究了科学史何以可能的问题,通过分析,文章得出结论:科学史在某方面是不可能的,但在某种意义上又是可能的,其缺点正是其所是的本质特征之一,对科学史进行评级也许不失为一种比较有效的使其得以可能的办法之一。     

概率论缘何没有起源于中国——基于赌博史的中西方考察

概率论在17世纪中叶起源于西方机会性赌博活动,有久远赌博历史的中国与概率论创立无缘,主要在于中西方赌博的目的、种类,对待赌博的态度、看待赌博结果等方面存在巨大差异,这种差异是对概率论缘何首先在西方而非中国起源的最好解释。概率论远滞后赌博起源是受其社会文化、道德及计算技术等因素的制约。     

A Simple Identification Proof for a Mixture of Two Univariate Normal Distributions

A simple proof of the identification of a mixture of two univariate normal distributions is given. The proof is based on the equivalence of local identification with positive definiteness of the information matrix and the equivalence of the latter to a condition on the score vector that is easily checked for this model. Two extensions using the same line of proof are also given. We would like to thank Tom Wansbeek, Michel Wedel, Arie Kapteyn, and two anonymous reviewers for helpful comments on earlier versions of this paper.     

An Unsupervised and Nonparametric Classification Procedure Based on Mixtures with Known Weights

I consider a new problem of classification into n(n ≥ 2) disjoint classes based on features of unclassified data. It is assumed that the data are grouped into m(M ≥ n) disjoint sets and within each set the distribution of features is a mixture of distributions corresponding to particular classes. Moreover, the mixing proportions should be known and form a matrix of rank n. The idea of solution is, first, to estimate feature densities in all the groups, then to solve the linear system for component densities. The proposed classification method is asymptotically optimal, provided a consistent method of density estimation is used. For illustration, the method is applied to determining perfusion status in myocardial infarction patients, using creatine kinase measurements.     

Oscillation Heuristics for the Two-group Classification Problem

We propose a new nonparametric family of oscillation heuristics for improving linear classifiers in the two-group discriminant problem. The heuristics are motivated by the intuition that the classification accuracy of a separating hyperplane can be improved through small perturbations to its slope and position, accomplished by substituting training observations near the hyperplane for those used to generate it. In an extensive simulation study, using data generated from multivariate normal distributions under a variety of conditions, the oscillation heuristics consistently improve upon the classical linear and logistic discriminant functions, as well as two published linear programming-based heuristics and a linear Support Vector Machine. Added to any of the methods above, they approach, and frequently attain, the best possible accuracy on the training samples, as determined by a mixed-integer programming (MIP) model, at a much smaller computational cost. They also improve expected accuracy on the overall populations when the populations overlap significantly and the heuristics are trained with large samples, at least in situations where the data conditions do not explicitly favor a particular classifier.     

基于增长曲线模型的R&D生产率测度研究

本文就企业R&D技术选择问题展开论述,认为企业R&D技术选择应着眼于比较不同技术R&D投入生产率,从而避免错误的R&D技术选择。为求得不同技术R&D投入生产率,作者对技术增长曲线模型进行了深入分析,并就具体的估计方法进行了卓有成效的探讨。     

中国前农业时期古人类的文明化进程探析

农业、新石器、定居、陶器是农业时期古人类行为及其实现途径的基本文化要素,四者构成的生产生活体系使人类获取食物和抵御外部威胁的能力得到极大提高,成为早期文明起源的文化基础。对这一生产生活体系在前农业时代的原初形态进行追溯,可以看到从渔猎采集到农业生产、从迁徙到定居生活、从火石工具到新石器、陶器工具转变的内在逻辑。而人类自身的生物性特征和在自然界中的弱质性地位是这一转变得以实现的重要动因之一。"善假于物"的人类生存智慧是古人类文明化进程中逐渐形成的原初文明因素,也是造成"人猿相揖别"的重要契机。     

Salmon and Van Fraassen on the Existence of Unobservable Entities: A Matter of Interpretation of Probability

A careful analysis of Salmon’s Theoretical Realism and van Fraassen’s Constructive Empiricism shows that both share a common origin: the requirement of literal construal of theories inherited by the Standard View. However, despite this common starting point, Salmon and van Fraassen strongly disagree on the existence of unobservable entities. I argue that their different ontological commitment towards the existence of unobservables traces back to their different views on the interpretation of probability via different conceptions of induction. In fact, inferences to statements claiming the existence of unobservable entities are inferences to probabilistic statements, whence the crucial importance of the interpretation of probability.