数学素质培养

文章从素质教育的要求出发,结合数学教学实践,着重阐述了数学素质的内涵及其特征,并就如何培养学生数学素质的初步探讨.     

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.     

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。     

北宋前中期富民阶层与诗词关系考论

北宋前中期富民阶层在经济政治"新变"背景下得到迅速发展,这一阶层的某些属性决定了富民必然有诗词消费需求。富民阶层的精神需求与群体心态,对诗词发展起到了重要的作用。为了满足富民阶层需要而写作的诗词,随之具有了某些较为固定的艺术特征。     

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.     

学术职业的道德特征与学术道德建设

学术职业具有其自身的道德特征,它以时代性、创造性、自由性、诚实性作为基本内核,从而构成了学术职业区别于其他社会职业类型的道德意识。学术道德建设不仅包括科学研究过程中的道德建设,还包括育人、教学、社会服务过程中的学术道德建设等多个方面。探讨学术职业的道德特征,旨在为学术道德建设提供理论基础。     

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.     

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。