WEIGHTED ANALYSIS OF PRINCIPAL COMPONENTS: TWO APPROXIMATIONS TO STATISTICAL WEIGHTS

Two approximate methods for weighted principal components analysis (WPCA) were devised and testedin numerical experiments using either empirical variances (obtained from replicated data) or assumedvariances (derived from unreplicated data). In the first ('spherical') approximation each data vector wasassigned a weight proportional to the geometrical mean of its variances in all dimensions. Thearithmetical mean of variances was used instead in the other approximation. Both the numericalexperiments with artificial data containing random errors of various kinds (constant, proportional,constant plus proportional, Poisson) and the analysis of two sets of Raman spectra clearly indicated thenecessity of introducing statistical weights. The spherical approximation was found to be slightly betterthan the arithmetical one. The application of statistical weighting was found to improve the performanceof PCA in estimation problems.     

Multi-criteria spatial screening and uncertainty analysis applied to direct-use geothermal projects

ABSTRACT

The focus of this work is general methods for prioritization or screening of project sites based on the favorability of multiple spatial criteria. We present a threshold-based transformation of each underlying spatial favorability factor into a continuous scale with a common favorability interpretation across all criteria. We compare several methods of computing site favorability and propagating uncertainty from the data to the favorability metrics. Including uncertainty allows decision makers to determine if seeming differences among sites are significant. We address uncertainty using Taylor series approximations and analytical distributions, which are compared to computationally intensive Monte Carlo simulations. Our methods are applied to siting direct-use geothermal energy projects in the Appalachian Basin, where our knowledge about any particular site is limited, yet sufficient data exist to estimate favorability. We consider four factors that contribute to site favorability: the thermal resource described by the depth to 80°C rock, natural reservoir productivity described by rock permeability and thickness, potential for induced seismicity, and the estimated cost of surface infrastructure for heat distribution. Those factors are combined in three ways. We develop favorability uncertainty propagation and sensitivity analysis methods. All methods are general and can be applied to other multi-criteria spatial screening problems.     

STATISTICAL F-TESTS FOR ABSTRACT FACTOR ANALYSIS AND TARGET TESTING

Fisher variance ratio tests are developed for determining(1)the number of statistically significantabstract factors responsible for a data matrix and(2)the significance of target vectors projected into theabstract factor space.F-tests,developed from the viewpoint of vector distributions,are applied tovarious data sets taken from the chemical literature.     

1961-2009 年国际主要粮食价格时间变化特征分析

本文首先介绍了基于国际粮食贸易的国际主要粮食价格测定方法,并用EVIEW 软件对国际主要粮食价格数据进行数据分离,在此基础上,采用谱分析法和数理统计方法分析了1961-2009 国际主要粮食价格的时间特征,总结和分析了国际主要粮食价格变化的趋势性、周期性和波动性特征。结果表明：①国际主要粮食价格趋势性明显,随时间呈现上涨趋势;②在多种因素的影响下,国际主要粮食价格存在着多周期性。③随着全球一体化和粮食金融化趋势的不断加强,国际主要粮食
价格不稳定性也越来越强。本文研究结果对于进一步分析国际粮食价格机制有一定的参考价值。     

Spectral estimation on a sphere in geophysics and cosmology

We address the problem of estimating the spherical-harmonic power spectrum of a statistically isotropic scalar signal from noise-contaminated data on a region of the unit sphere. Three different methods of spectral estimation are considered: (i) the spherical analogue of the one-dimensional (1-D) periodogram, (ii) the maximum-likelihood method and (iii) a spherical analogue of the 1-D multitaper method. The periodogram exhibits strong spectral leakage, especially for small regions of area   A ≪ 4π  , and is generally unsuitable for spherical spectral analysis applications, just as it is in 1-D. The maximum-likelihood method is particularly useful in the case of nearly-whole-sphere coverage,   A ≈ 4π  , and has been widely used in cosmology to estimate the spectrum of the cosmic microwave background radiation from spacecraft observations. The spherical multitaper method affords easy control over the fundamental trade-off between spectral resolution and variance, and is easily implemented regardless of the region size, requiring neither non-linear iteration nor large-scale matrix inversion. As a result, the method is ideally suited for most applications in geophysics, geodesy or planetary science, where the objective is to obtain a spatially localized estimate of the spectrum of a signal from noisy data within a pre-selected and typically small region.     

基于SCI-E的2010—2014年美国海洋学研究热点分析

基于科学引文索引数据库SCI-E, 检索获得2010—2014年美国海洋学研究型文献9 702篇, 在确定文献集中词频不低于40的54个高频关键词基础上, 运用共词分析法, 以SPSS 20.0为工具, 探索美国近5年海洋学研究热点。结果表明, 2010—2014年间美国海洋学研究热点集中在6大主题领域: 海洋环流动力学研究、海洋灾害研究、科学技术和方法在海洋中的应用研究、海洋初级生产力研究、海洋污染研究、海洋生物多样性研究。在此基础上, 运用社会网络分析法, 借助可视化工具Ucinet, 对6大研究主题和高频作者共现矩阵进行可视化, 揭示出各研究主题的作者团体。     

EXAMINING LARGE DATABASES:A CHEMOMETRIC APPROACH USING PRINCIPAL COMPONENT ANALYSIS

Principal component analysis is used to examine large multivariate databases.The graphical approachto exploratory data analysis is described and illustrated with a single example of chemical compositiondata obtained on environmental dust particles.While the graphical approach to exploratory data analysishas certain advantages over the numerical procedures,the empirical approach described here should beviewed as complementary to the more robust treatments that statistical methodologies afford.     

和平沟滑坡风险性评价

本文从工程可靠性出发，对和平沟滑坡可能的失稳规模、方式及其危害性进行了深入分析。初步估算出该滑坡的危险性（风险）概率，否定了该滑坡治理的必要性，从而为国家节约了可观的建设资金。这一分析思路地其他工程有一定的借鉴意义。     

WINDOW FACTOR ANALYSIS:THEORETICAL DERIVATION AND APPLICATION TO FLOW INJECTION ANALYSIS DATA

Window factor analysis(WFA)is a self-modeling method for extracting the concentration profiles ofindividual components from evolutionary processes such as flow injection,chromatography,titrationsand reaction kinetics.The method takes advantage of the fact that each component lies in a specificregion along the evolutionary axis,called the‘window’.Theoretical equations are derived.The methodis used to extract the concentration profiles and spectra of seven bismuth species from data obtained byGemperline and Hamilton,who injected bismuth perchlorate into a flowing stream of hydrochloric acid.     

CAN IMAGE ANALYSIS PROVIDE INFORMATION USEFUL IN CTTEMISTRY?

Images can contain chemical information and many chemical methods can generate image data. For anefficient extraction of chemical data from images, data analysis techniques are necessary, It is a greatadvantage to be able to work on multivariate images. Many imaging techniques allow the extraction ofchemical information. Inorganic analytical chemistry seems to have the longest tradition here, butorganic chemistry and biochemistry may soon be catching up. Also large data arrays from non-imagingtechniques can be combined with image analysis in a useful way, provided certain conditions are fulfilled.     

CORRESPONDENCE ANALYSIS AND ADSORBATE SELECTION FOR CHEMICAL SENSOR ARRAYS

Carey et al.utilized principal components analysis (PCA) to analyze frequency shift data obtained frompiezoelectric sensors formed by coating quartz crystals with 27 different GC stationary phases and testedusing 14 analytes.The objective of the analysis was to determine an optimal reduced set of coatings fordetection of the analytes.The results were correlated with those obtained from cluster analysis.In thispaper the data are re-analyzed using correspondence analysis (CA).The advantage of using CA includea symmetric treatment of sensor coatings and analytes and better identification of the representation ofthe analytes in terms of the detection components.The results obtained by the conjunctive use of PCA,a varimax rotation and cluster analysis were obtained by CA.     

Spatial Social Network Analysis of Resource Access in Rural South Africa

Communities in the rural developing world often sit at the margin of market, migration, and technology exchanges. They are arguably becoming more interconnected and networked than ever before. This article seeks to expand on an understanding of natural resource access in the rural developing world by combining social network analysis (SNA) data and geographic position data obtained via Global Positioning System (GPS) and participatory mapping in rural South Africa. This work therefore utilizes a sociospatial framework in understanding natural resource use and access in a community-level analysis. Notably, in our study we find very little association among natural resource use, access, and social position with even the most tolerant measure but enough association so as not to dismiss the relationship completely. We believe that our results can inform investigations of both resource access and social network position and conclude that a subsequent possibilist approach to human–environmental interactions would be an ideal framework for this methodology and potentially for sociospatial studies more widely.     

黄土孢粉分析的新途径——筛滤分析法

黄土-古土壤序列在全球古气候、古环境研究中占有不可替代的重要地位,而其中的孢粉是黄土高原生态环境演化过程中保存的直接生物学证据,它对建立黄土高原降水或湿度状况的时空变化特征,认识季风变迁的过程、规律以及未来发展趋势等具有重要的意义。随着黄土研究工作的不断深入,作为直接生物学证据的孢粉研究相对薄弱。其中最困扰的因素是从黄土中提取孢粉极其困难,分析技术上始终未能找到一个突破口,因此需要一种分析效果好、快捷、成本低的分析方法以获得大量高精度的孢粉数据。筛滤分析法正是为了适应黄土研究的需要而设计的一种新型的黄土孢粉分析方法。筛滤分析法利用真空状态下的气压差使样品在水中完全悬浮跳动,样品得到充分的冲洗并促使孢粉与其它无机质与有机质分离。相对真空的状态减少了微细颗粒对极为细小的网眼的阻塞,重力作用促使水及各类颗粒不断冲击筛网,使粒径小于10μm的物质较容易被过滤到聚水容器中,而孢粉与较少的大颗粒物质则被隔离在筛网之上,这使我们很容易用重液浮选出干净、清晰的孢粉底样。筛滤分析法与常规的黄土孢粉分析相比,具有以下特点:①大大降低了分析样品的重量及药品的消耗,一般仅需样品30 g左右,是常规分析法用量的1/6~1/8。②整个分析流程短, 12个样品一个流程仅需3~4 d。③筛滤分析法使孢粉几乎全部被隔离在筛网上而丢失极少,提高了黄土孢粉研究精度。④筛滤分析法几乎不破坏孢粉的结构,孢粉底样干净、清晰。使用筛滤分析法共分析耀县全新世黄土剖面69块孢粉样品,均发现数量不等的孢粉。孢粉底样干净、杂质少,结构清楚。共统计孢粉14978粒,分属27个科属,这些科属包括了黄土高原主要的孢粉类型。从孢粉结果可以初步确定,在全新世时期,位于黄土高原南缘的耀县地区,草本植物占全部孢粉总量的93.6%,而乔木植物仅占孢粉总量的4.7%。在整个剖面中没有出现乔木植物含量超过30%,可以认为在黄土高原的全新世时期是以草原植被为主,并无森林生长。     

Vegetation patterns and diversity along an altitudinal and a grazing gradient in the Jabal al Akhdar mountain range of northern Oman

Little is known about the effects of grazing on vegetation composition on the Arabian Peninsula. The aim of this study therefore was to analyse the vegetation response to environmental conditions of open woodlands along an altitudinal and a grazing gradient in the Jabal al Akhdar mountain range of Oman. The species composition, vegetation structure, grazing damage and several environmental variables were investigated for 62 samples using a nested plot design. Classification analysis and a Canonical Variate Analysis (CVA) were used to define vegetation types and to identify underlying environmental gradients. The relationship between environmental variables and diversity was analysed using correlation coefficients and a main-effects ANOVA. The plant species richness followed a unimodal distribution along the altitudinal gradient with the highest number of species at the intermediate altitudinal belt. The cluster analysis led to five vegetation groups: The Sideroxylon mascatense–Dodonaea viscosa group on grazed and the Olea europaea–Fingerhuthia africana group on ungrazed plateau sites at 2000 m a.s.l., the Ziziphus spina-christi–Nerium oleander group at wadi sites and the Moringa peregrina–Pteropyrum scoparium group at 1200 m a.s.l, and the Acacia gerrardii–Leucas inflata group at 1700 m a.s.l. The CVA indicated a clear distinction of the groups obtained by the agglomerative cluster analysis. The landform, altitude and grazing intensity were found to be the most important variables distinguishing between clusters. Overgrazing of the studied rangeland is an increasing environmental problem, whereas the plant composition at ungrazed sites pointed to a relatively fast and high regeneration potential of the local vegetation.     

湖南省产业结构对生态环境的影响分析

运用转移份额分析法与主成分分析法分别测算了产业结构效应系数和生态环境质量综合指数,进而通过建立动态计量模型分析了湖南省产业结构对生态环境的作用机制。研究指出,近20年来,湖南省产业结构优化水平不断提高的同时,生态环境综合质量也在稳步提高。产业结构效应系数与生态环境各指数存在长期的动态均衡关系,无论从短期还是长期来看,产业结构对生态环境压力、状态、响应及综合质量均具有显著的促进作用,但产业结构对生态环境的积极影响大于其带来的环境压力;产业结构变迁是影响总体环境质量的关键因素。积极转变经济增长方式、促进产业结构优化是较为理想的政策选择。     

MIXTURE ANALYSIS USING FACTOR ANALYSIS.Ⅱ:SELF-MODELING CURVE RESOLUTION

One of the major applications of factor analysis in the chemical literature,self-modeling curve resolution(SMCR),is covered in this review,including a historical account of the inethods derived from Lawtonand Sylvestre's original method.Papers treating the theory or applications of SMCR are included.Qualitative and quantitative applications are described where appropriate.     

Integrated Spatial and Spectrum Method for Geochemical Anomaly Separation

A new approach for separating geochemical anomalies from background has been developedon the basis of integration of spatial and spectrum analysis. A map generated from geochemicaldata can be transformed into a frequency domain in which a spatial concentration-area fractalmethod can be applied to distinguish the patterns on the basis of the power-spectrum distribution.Distinct classes can be generated, such as lower, intermediate, and high power-spectrum valuesapproximately corresponding to background, anomalies, and noises of geochemical values ina spatial domain. An irregular filter then can be constructed on these distinct patterns withthe background and noises related to low- and high-power-spectrum values being removed.The image converted back to a spatial domain with the filter applied can show patterns which,after the removal of background and noise, mainly reflect a residual area that representsanomalous or atypical geochemical patterns. This method is demonstrated using a case studyof soil geochemical data from the Mudik area, on the island of Sumatra, Indonesia. The resultsobtained from this method in comparison with those obtained from other methods have shownthat the newly developed method can separate overlapping populations without using a singlecutoff value.     

GIS与地理分析

GIS与地理学的结合 ,有助于地理学家分析区域性或全球性一系列的地理问题 ,研究大气圈、水圈、岩石圈、生物圈等圈层内部的结构特征、分布规律、演化过程以及彼此之间物质流、能量流、信息流的传递方式及动力学机制。