休谟与启蒙运动——基于《人性论》引言的思想史考察

当前对休谟的研究常把他和启蒙运动相隔裂.通过对休谟代表性著作《人性论》引言的分析,可以发现他和法国启蒙思想家共享认识世界的“力学模式”和实验方法,都试图将当时在英格兰兴起的“自然哲学”应用于人类境况,都致力于用对人类生活有用的经验研究所产生的新理论代替传统形而上学.同时,休谟对经验主义方法自身的局限有着更为健全的认识,主张在经验和可观察现象范围内的实验方法.这一认识在我们反思启蒙时极富价值.     

The empirical Bayes estimators of the parameter of the Poisson distribution with a conjugate gamma prior under Stein's loss function

For the hierarchical Poisson and gamma model, we calculate the Bayes posterior estimator of the parameter of the Poisson distribution under Stein's loss function which penalizes gross overestimation and gross underestimation equally and the corresponding Posterior Expected Stein's Loss (PESL). We also obtain the Bayes posterior estimator of the parameter under the squared error loss and the corresponding PESL. Moreover, we obtain the empirical Bayes estimators of the parameter of the Poisson distribution with a conjugate gamma prior by two methods. In numerical simulations, we have illustrated: The two inequalities of the Bayes posterior estimators and the PESLs; the moment estimators and the Maximum Likelihood Estimators (MLEs) are consistent estimators of the hyperparameters; the goodness-of-fit of the model to the simulated data. The numerical results indicate that the MLEs are better than the moment estimators when estimating the hyperparameters. Finally, we exploit the attendance data on 314 high school juniors from two urban high schools to illustrate our theoretical studies.     

切线模量法确定强夯地基承载力的现场试验研究

平板载荷试验是检验强夯加固填土地基承载力的重要手段，基于平板载荷试验的切线模量法以安全系数和允许沉降两个控制因素结合Terzaghi极限承载力理论可计算不同沉降要求的地基承载力。为了验证切线模量法计算强夯地基承载力的可行性和优越性，对现场填土地基进行强夯加固后进行平板载荷试验和超重型动力触探试验，以三组[WTBX]平板载荷试验9个试验点的测试结果为基础，反演该地基土性参数并通过切线模量法绘制p s曲线，发现切线模量法计算的p s曲线与现场p s曲线能够很好的吻合，故可用切线模量法计算基础中心不同沉降量所对应的地基承载力,且能够弥补平板载荷试验和动力触探测试方法的不足，故为浅基础的设计提供了一条新的途径。     

Inclusion of persons with disabilities in mainstream employment: is it really all about the money? A case study of four large companies in Norway and Sweden

This study investigates how large companies respond to public policy measures to ensure the inclusion of persons with disabilities in mainstream employment based on a case study of four companies in Norway and Sweden. The qualitative interviews, which were conducted with company managers, government representatives in Norway, and non-governmental organisations in Sweden, revealed three overarching themes: (1) ‘legitimacy’, (2) ‘financial interests’ and (3) ‘non-financial support’. The results indicate a more proactive response from the Swedish companies, especially regarding persons with intellectual and learning difficulties. The Norwegian companies reveal a high commitment to their own employees. These findings cannot be explained solely using neo-institutional theory, which holds that organisations demonstrate ‘conformity with powerful institutional myths to strengthen support and secure survival'. The results indicate that inclusive targeted corporate policies and programmes, advisory support, and the agency and value choices of the management might matter more.     

分数阶长短波方程的整体光滑解

本文研究了分数阶长短波方程组的周期初边值问题,运用一致先验估计和Galerkin方法证明了分数阶长短波方程整体光滑解的存在性和唯一性.     

Tests for generalized exponential laws based on the empirical Mellin transform

Recently, many standard families of distributions have been generalized by exponentiating their cumulative distribution function (CDF). In this paper, test statistics are constructed based on CDF–transformed observations and the corresponding moments of arbitrary positive order. Simulation results for generalized exponential distributions show that the proposed test compares well with standard methods based on the empirical distribution function.     

Best-worst multi-criteria decision-making method: Some properties and a linear model

The Best Worst Method (BWM) is a multi-criteria decision-making method that uses two vectors of pairwise comparisons to determine the weights of criteria. First, the best (e.g. most desirable, most important), and the worst (e.g. least desirable, least important) criteria are identified by the decision-maker, after which the best criterion is compared to the other criteria, and the other criteria to the worst criterion. A non-linear minmax model is then used to identify the weights such that the maximum absolute difference between the weight ratios and their corresponding comparisons is minimized. The minmax model may result in multiple optimal solutions. Although, in some cases, decision-makers prefer to have multiple optimal solutions, in other cases they prefer to have a unique solution. The aim of this paper is twofold: firstly, we propose using interval analysis for the case of multiple optimal solutions, in which we show how the criteria can be weighed and ranked. Secondly, we propose a linear model for BWM, which is based on the same philosophy, but yields a unique solution.     

Inferences on functions of Pareto parameters with application to income inequality measures

The Theil, Pietra, Éltetö and Frigyes measures of income inequality associated with the Pareto distribution function are expressed in terms of parameters defining the Pareto distribution. Inference procedures based on the generalized variable method, the large sample method, and the Bayesian method for testing of, and constructing confidence interval for, these measures are discussed. The results of Monte Carlo study are used to compare the performance of the suggested inference procedures from a population characterized by a Pareto distribution.     

Statistical estimation of internal available bandwidth

This paper presents a method for using end-to-end available bandwidth measurements in order to estimate available bandwidth on individual internal links. The basic approach is to use a power transform on the observed end-to-end measurements, model the result as a mixture of spatially correlated exponential random variables, carryout estimation by moment methods, then transform back to the original variables to get estimates and confidence intervals for the expected available bandwidth on each link. Because spatial dependence leads to certain parameter confounding, only upper bounds can be found reliably. Simulations with ns2 show that the method can work well and that the assumptions are approximately valid in the examples.     

Bivariate symbolic regression models for interval-valued variables

Interval-valued variables have become very common in data analysis. Up until now, symbolic regression mostly approaches this type of data from an optimization point of view, considering neither the probabilistic aspects of the models nor the nonlinear relationships between the interval response and the interval predictors. In this article, we formulate interval-valued variables as bivariate random vectors and introduce the bivariate symbolic regression model based on the generalized linear models theory which provides much-needed exibility in practice. Important inferential aspects are investigated. Applications to synthetic and real data illustrate the usefulness of the proposed approach.