电力市场理论的若干基本概念辨析

本文通过对电力市场、电价与电力交易模式等电力经济基础概念的分析,指出了现有概念体系的不足,并提出了作者的认识,尤其是对电力市场一般与市场特殊作出详尽分析,力图为构建竞争性的电力市场经济理论奠定微观概念的基础。     

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.     

从语用学的视角看隐喻之意义

传统隐喻理论中比较有代表性的比较理论和互动理论都从纯粹的语义学角度解释隐喻。本文在证明此种途径的偏颇和不足的同时,将隐喻置于语用学的视野,结合隐喻使用中所涉及的语境等诸多因素以及会话含义理论来探索隐喻的语用学解释途径。     

造粒塔内液滴传热数学模型的建立

通过在竖直向上流动的空气中逆向运动的颗粒的速率方程．单颗粒与流动气流间的Ranz和Marshall传热关联式．以及能量守恒方程和传热速率方程建立简化的液滴粒径与塔高间的定量关系．从而为研究喷雾造粒工艺提供参考．     

从“生活空间”到“文学空间”——“空间理论”:作为文学批评方法

文学空间来源于生活空间,文学空间是生活空间的变型、转化和升华。生活空间要转化成文学空间必须经过作家的遴选、厘定和创造并且包蕴着作家的审美观、世界观和人文观。"空间理论"立足于从生活空间向文学空间的过渡,充分发掘作家的空间想象方式及其表现手段,探讨作家内心世界的外化规律和价值取舍。     

女性"隐形"地位的多元认知透视

在男性占主导地位的语言,诚如英汉语中"乞丐""医生"等职业术语和"chairman""hero"等官衔荣誉称呼之类的名词,一般性的人类泛指"a man","mankind"以及代词的非指示用法中,女性往往被置于"隐形"的地位。性别差异和性别歧视的现象已引起社会上各学科的普遍关注,然而,从认知角度对这一现象作出注解的文章寥寥。运用认知语言学中的原型和范畴理论、框架理论、心理空间和概念合成理论对此予以阐释,可为英汉语中这一现象的理论阐释提供全新的多元认知视角。     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.     

信度函数在政府形象评价模型中的应用

在分析政府形象效能评价系统和信息置信度的基础上,建立了基于信度函数的政府形象评价模型。运用该函数建模分析了政府形象评估中的理念识别系统、行为识别系统、视觉识别系统、环境识别系统以及个人识别系统等五大不确定性评价问题。经过理论分析,该函数对政府形象的评估有较大的参考价值。此外,该函数也可以用于对其他类似复杂性系统的效能评估,具有普遍适用性。     

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.     

Detection and correction of artificial shifts in climate series

Summary.  Many long instrumental climate records are available and might provide useful information in climate research. These series are usually affected by artificial shifts, due to changes in the conditions of measurement and various kinds of spurious data. A comparison with surrounding weather-stations by means of a suitable two-factor model allows us to check the reliability of the series. An adapted penalized log-likelihood procedure is used to detect an unknown number of breaks and outliers. An example concerning temperature series from France confirms that a systematic comparison of the series together is valuable and allows us to correct the data even when no reliable series can be taken as a reference.