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。     

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.     

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。     

上市公司虚减成本费用的方法分析

中国证券市场尚不完善 ,上市公司操纵利润的现象屡见不鲜。虚减成本费用是上市公司调增利润更简便的方法。在财务运作中 ,上市公司频繁运用虚拟资产、利息资本化等五种方法虚减成本费用     

管理案例教学法的探析

管理案例教学法是现代管理学教育中不可替代的重要方法 ,是目前大学教育中弥补学生管理实践不足、锻炼提高学生学会管理本领的重要手段 ,同时也是促进教师素质提高的重要途径。本文对此试作探析。     

多媒体英语教学的优势

本文旨在通过提出多媒体教学手段的多种优势以及诸多专家学者的观点,同时谈到笔者在使用多媒体进行外语教学过程中的一些切身体会,进行理论和实践上的论证,以发掘外语教学中利用多媒体教学手段进行创新性“教”与自主性“学”的可能性,并进一步加强学生的自主性学习以及自我调节性学习,使外语教师更加高效地利用多媒体的优势进行理想的外语教学,同时使外语教学手段更加具有开放性和实践性。     

Geometric Method and Generalized Linear Models. Two Opposite Multiparametric Approaches Illustrated on a Sample of Pituitary Adenomas

We used two statistical methods to identify prognostic factors: a log-linear model (logistic and COX regression, based on the notions of linearity and multiplicative relative risk), and the CORICO method (ICOnography of CORrelations) based on the geometric significance of the correlation coefficient. We applied the methods to two different situations (a "case-control study' and a "historical cohort'). We show that the geometric exploratory tool is particularly suited to the analysis of small samples with a large number of variables. It could save time when setting up new study protocols. In this instance, the geometric approach highlighted, without preconceived ideas, the potential role of multihormonality in the course of pituitary adenoma and the unexpected influence of the date of tumour excision on the risk attached to haemorrhage.