PRINCIPAL COMPONENT ANALYSIS APPLIED TO THE STUDY OF SUCCESSIVE COMPLEX FORMATION DATA IN CU(II)-ETHANOLAMINE SYSTEMS

Application of principal component analysis to Cu(II)-ethanolamine complex formation data is shown.Determination of the number of complex species is obtained from the rank of the matrix of spectral datausing either Gauss elimination or factorial analysis.Relevant information concerning species distributionversus pH is obtained from the plot of the signficant factors upsurging from the evolution of spectraltitration data.     

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.     

EVOLVING FACTOR ANALYSIS APPLIED TO FLOW INJECTION ANALYSIS DATA

Evolving factor analysis is used to estimate the concentration profiles and spectra of Bi~(3 )and the bismuthchloride complexes BiCl~(2 )through BiCl_6~(3-)formed by injection of bismuth percblorate into a flowingstream of 1.0 mol l~(-1) HCl.The estimated spectra compare favorably with previously published spectraof the complexes.     

ASSESSMENT OF THE EFFECTIVE RANK OF A (CO)VARIANCE MATRIX: A NON-PARAMETRIC GOODNESS-OF-FIT TEST

Each eigenvector of the dispersion matrix[X]~T[X]was shown to be a partial predictor of the originaldata matrix [X],the sum of the predictions from the individual principal components being equal to theexpectance of [X].By comparing the distributions of the members of two neighbouring predictedmatrices,[X]_(1...i)and [X](1...i+1)(i.e.the sums of the first i and i+1 individual predictions respectively),it was shown that they should be indistinguishable provided that i is equal to or greater than the effectiverank of [X],and significantly different otherwise.This was confirmed by analysing the visible absorptionspectra of methyl orange and methyl red solutions as well as the Raman spectra of Na_2SO_4 and MgSO_4solutions.On the grounds of these findings,a non-parametric goodness-of-fit test for assessing theeffective rank of[X]was proposed which proved to be comparatively conservative and more robust thanmost currently used tests.     

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.     

SHORT COMMUNICATION THE RELATIONSHIP OF CLOSURE,MEAN CENTERING AND MATRIX RANK INTERPRETATION

This paper describes an investigation into the relationship of closure,a baseline offset and mean centeringto the interpretation of matrix rank.The equivalence of a certain type of closure to a constant baseline(i.e.a simple numerical offset which may vary between response channels but is constant over all samples)is demonstrated.A systematic approach to the interpretation of the rank of a matrix is given.     

REAL-TIME FILTERING OF DATA FROM MOBILE,PASSIVE REMOTE INFRARED SENSORS WITH PRINCIPAL COMPONENT MODELS OF BACKGROUND

Real-time monitoring of pollutant levels from a mobile measuring platform requires fast,flexible dataanalysis methods.This paper reports a method for rapid analysis of passive remotely sensed infrared datawith the aid of a Kalman filter.The background spectra produced by emission from the atmosphere aremodelled at the start of the data collection sequence with a simple principal components model obtainedby eigenanalysis of the initial‘blank’data taken with the spectrometer.The species of interest areincluded in the state space model by a separate measurement of their infrared spectra.It is demonstratedthat for best filter performance in detecting the simulated pollutant species SF_6 in the atmosphere,a filtermodel with two principal components describing the emission background works best.The filter‘maps’of SF_6 closely follow the integrated spectral intensities measured after removal of suitable backgrounds.     

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.     

SHORT COMMUNICATION TARGET FACTOR ANALYSIS:UV SPECTROPHOTOMETRY FOR THE SIMULTANEOUS DETERMINATION OF SIX AMINO ACIDS

The UV spectra of mixture solutions consisting of tyrosine,tryptophane,phenylalanine,cystine,histidineand 3,4-dihydroxyl phenylalanine have been measured.The numbers,identities and concentrations of theamino acids in the mixtures have been determined successfully using target factor analysis.The effectsof the wavelength range and the selected sampling interval on the results are discussed.Twenty-fivesynthetic mixture samples have been analysed successfully.The average recoveries are 98·9 for Tyr,96·5for Trp,105·6 for Phe,98·1 for Cys,98·9 for His and 106·4 for Di-phe.The results obtained are ingood agreement with those obtained by the Kalman filter method.     

西南极菲尔德斯半岛地壳形变监测的数据处理与分析

为了研究南极现代地壳运动,中国在西南极菲尔德斯海峡地区布设了形变监测网,并用ＤＩ－２０测距仪和ＧＰＳ定位仪对该网进行了监测。同时,中国也参加了ＳＣＡＲ组织的全南极ＧＰＳ联测。本文讨论了将形变参数纳入误差方程的水平形变数据处理方法,并对刚体平移、旋转、均匀应变几种典型形变模型在测边网平差中的运用进行了讨论。通过对经典自由网与秩亏自由网的基准分析,提出对形变参数以及其它附加参数和点位参数分别给定参考基准的方法。相应于上述方法,编制了一系列数据处理程序并将之应用于对西南极菲尔德斯海峡形变监测网的数据分析。本文还利用监测网应变分析原理,对ＧＰＳ监测数据进行了讨论和分析,结果表明,菲尔德斯断裂地区存在微小的断裂剪切运动,但位移量不大。     

中国智力资源空间分布及其影响因素研究

现代社会已步入知识经济时代。知识经济显著特点就在于信息、知识等各种类型的智力资源取代工业经济的资本上升成为新的、决定性的终极资源和核心生产要素。在研究智力资源涵义的基础上，选取了投入、产出、环境支持、智力资源4个系统30个不同指标，运用数理统计方法中的因子分析来定量研究中国智力资源空间分布特点，从而进一步分析出影响中国智力资源的空间分布的4个主要因素：经济发展程度、行政区标准问题、历史因素和区域文化模式不同。     

DRIED GRASS SILAGE ANALYSIS BY NIR REFLECTANCE SPECTROSCOPY-A COMPARISON OF STEPWISE MULTIPLE LINEAR AND PRINCIPAL COMPONENT TECHNIQUES FOR CALIBRATION DEVELOPMENT ON RAW AND TRANSFORMED SPECTRAL DATA

Calibrations to predict crude protein (CP) and in vitro dry matter digestibility (IVDMD) in dried grasssilage from reflectance data collected at 19 wavelengths on an InfraAlyzer 400R have been developedusing stepwise multiple linear (SML) and principal component (PC) regression techniques. A directcomparison of the efficacy of each multivariate technique in this application has been possible by usingidentical calibration development and evaluation sample sets. The effect of two data transformation stepsprior to PC regression was also investigated. PC regression of raw reflectance data yielded no significantimprovement in the standard errors of prediction (SEP) for CP and IVDMD over those obtained bySMLR, viz. 0.61 vs 0.63 and 2.9 vs 3.0 respectively. Computation time for development and evaluation ofthe PC regression equation was less than for selection of the best SMLR equation, and PCR equationsmay be more robust. Data transformation to reduce granularity effects prior to PCR did not produce anyimprovement in predictive accuracy for either IVDMD or CP.     

地理信息系统发展趋势

本文根据国内外在地理信息系统方面的进展，就地理信息系统的科学概念、基本构成和它的以下一些发展趋势作了讨论：（1）地理信息系统是构成地理学日臻完善的技术体系的重要部分；（2）空间分析功能是系统研究和应用的主要目标；（3）系统最重要的技术问题是管理和存储大量空间数据的数据结构；（4）综合性的发展特色日益明显；（5）标准化和智能型的发展方向已引起关注。