关于物流的科学分类问题（续）

本文最新提出物流最基本的四个固有属性：物（Material）的根本属性，流（Flow）的浪本属性，物和流的主体（Party）属性，物和流的地域（Region）属性。无论自然界物流，还是社会界物流，经济界物流，都具有这四个方面属性（RPMF）。同时，本文首次提出物流四要素RPMF原理。根据物流四要素RPMF原理，提出按各要素的不同属性对物流进行科学分类的方法，并给出物流分类图。     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

优选方案定量评价模型研究

在确定评价指标体系的基础上，如何对若干事物或方案进行选优是一个十分有意义的问题．作者利用模糊多目标决策对此进行研究，并通过实例说明该方法的有效性与实用性．     

教育世界的特性

教育世界是教育科学研究的对象域。教育世界的特性是本质世界。教育世界的本质世界特性是以人的本质力量的外在表现物——哲学和各门学科知识体系为手段培养人性——人的本质。教育世界的本质特点就是本质教育。人的本质表现在责任、方法和美。教育世界的本质世界特性决定了教育科学属于本质科学。     

无因管理问题的研究

无因管理作为民法法律之债的发生依据之一,应当根据社会的发展赋予其新的价值。本文试从无因管理的社会意义和法律性质、成立条件、效力、类型化及类型化无因管理的法律效果等方面就无因管理的有关问题进行了研究。     

HEAVY-TAILED-DISTRIBUTED THRESHOLD STOCHASTIC VOLATILITY MODELS IN FINANCIAL TIME SERIES

To capture mean and variance asymmetries and time‐varying volatility in financial time series, we generalize the threshold stochastic volatility (THSV) model and incorporate a heavy‐tailed error distribution. Unlike existing stochastic volatility models, this model simultaneously accounts for uncertainty in the unobserved threshold value and in the time‐delay parameter. Self‐exciting and exogenous threshold variables are considered to investigate the impact of a number of market news variables on volatility changes. Adopting a Bayesian approach, we use Markov chain Monte Carlo methods to estimate all unknown parameters and latent variables. A simulation experiment demonstrates good estimation performance for reasonable sample sizes. In a study of two international financial market indices, we consider two variants of the generalized THSV model, with US market news as the threshold variable. Finally, we compare models using Bayesian forecasting in a value‐at‐risk (VaR) study. The results show that our proposed model can generate more accurate VaR forecasts than can standard models.     

Horwitz's rule, transforming both sides and the design of experiments for mechanistic models

Summary. The paper develops methods for the design of experiments for mechanistic models when the response must be transformed to achieve symmetry and constant variance. The power transformation that is used is partially justified by a rule in analytical chemistry. Because of the nature of the relationship between the response and the mechanistic model, it is necessary to transform both sides of the model. Expressions are given for the parameter sensitivities in the transformed model and examples are given of optimum designs, not only for single-response models, but also for experiments in which multivariate responses are measured and for experiments in which the model is defined by a set of differential equations which cannot be solved analytically. The extension to designs for checking models is discussed.     

山西常家兴衰与人力资源优化

“常家”兴衰与人力资源的演变有着密切关系 ,常家在优化人力资源方面的一些主要措施 ,揭示出人力资源与经济发展是密不可分的。面对现代经济发展中遇到的种种挑战 ,更让我们认识到重视人力资源优化的重要性。以史为鉴 ,给现代人以很多启示。     

Real nonparametric regression using complex wavelets

Summary.  Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the discrete wavelet transform of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; then invert the discrete wavelet transform to form an estimate of the true underlying curve. Various researchers have proposed increasingly sophisticated methods of doing this by using real-valued wavelets. Complex-valued wavelets exist but are rarely used. We propose two new complex-valued wavelet shrinkage techniques: one based on multiwavelet style shrinkage and the other using Bayesian methods. Extensive simulations show that our methods almost always give significantly more accurate estimates than methods based on real-valued wavelets. Further, our multiwavelet style shrinkage method is both simpler and dramatically faster than its competitors. To understand the excellent performance of this method we present a new risk bound on its hard thresholded coefficients.     

基于主成分分析的我国西部地区间产业结构转换能力评价

产业结构的演进和转换是经济发展的本质特征,也是促进经济持续稳定协调发展的关键。西部地区产业结构转换能力的地区差异十分明显,本文阐述了影响地区产业结构转换的一般因素,并通过主成分分析方法对影响西部地区产业结构转换的主要因素进行了分析,并对西部各地区产业结构转换能力、转换速度以及转换方向进行了分析评价。