The potential of integrated modelling in conservation biology: A case study of the black‐footed albatross (Phoebastria nigripes)

Conservation biology aims at assessing the status of a population, based on information which is often incomplete. Integrated population modelling based on state‐space models appears to be a powerful and relevant way of combining into a single likelihood several types of information such as capture‐recapture data and population surveys. In this paper, the authors describe the principles of integrated population modelling and they evaluate its performance for conservation biology based on a case study, that of the black‐footed albatross, a northern Pacific albatross species suspected to be impacted by longline fishing     

无限家园--读廖志理的组诗《来自生活最初的激情》

文章通过解读组诗文本,抓住家园情结这一内核,较为翔实地剖析了诗人对农耕民族的精神历程与诗意关怀,并归纳了三个艺术特点即忧患精神的张扬、时空转换的把握和整体象征的艺术自觉.     

论老建筑再生与城市空间品质的塑造

通过老建筑再生对于城市的价值意义的研究以及对城市与老建筑关系的分析，从多个角度阐述由老建筑再生所带来的城市意象、城市肌理、场所精神、城市色彩、城市风貌等要素的变化及其促进城市空间品质的提高，并结合国内外案例对这一观点行论证。     

基于时变参数的中国总量生产函数估计

总量生产函数是宏观经济增长分析和技术进步定量化测算的基础,传统方法估算总量生产函数具有很多不足之处。利用1952—2005年中国宏观经济数据,建立时变参数模型,应用卡尔曼滤波算法,对我国1952—2005年间历年的总量生产函数进行了估算。研究结果表明:利用时变参数估算生产函数较好地捕捉到了经济政策的重大事件对于总量生产函数的影响,可能是理论与实际情况更加接近的一种拟合。我国技术进步和资本、劳动的产出弹性三者相互影响,呈同方向变化,并且技术进步对资本的产出弹性影响较大,对劳动的产出弹性影响较小,1978—2005年间我国属于节约资本型技术进步。     

论唐代山水题画诗的时空艺术

唐代题画诗审美时空的层次构成具有多重性,它融合了客观物理时空和中国画时空的特性,成为一种特殊的诗歌审美时空。在唐代山水题画诗中,诗人对画面时间二度审美,将画面凝固性的时间转化为永恒性和超越性的时间,给画面时间赋予了生命意识内涵。唐代山水题画诗中的空间则具有广远性和包容性的审美特点。广远性的特点显示出中国诗与画在空间意识上的相通,包容性则不但体现了诗人对绘画空间的二度审美,而且折射出诗人主体对外在空间驾驭、掌握乃至与其融合的理想。唐代山水题画诗隐逸的诗旨和诗中所表现出来的迷茫心态,体现了中国画时空的不确定性所造成的审美心理效应。     

基于经济时空的中国林业产业发展路径

经济时间和经济空间是研究产业变迁的两个重要维度,就林业产业时空特性而言,中国林业产业的发展面临着时空分离和时空压缩的困境。在经济全球化进程中,林业产业要适应现代科技变革和产业变迁,必须寻求新的发展路径:实现林业产业的时空转换,拓宽林业产业的市场时空;提高林业产业技术,促进林业产业的时空延伸;优化林业产业布局,提高林业产业的时空效益。     

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“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。     

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.