multivariate statistical analysis
Multivariate Statistical Analysis of Large Datasets: Single Particle Electron Microscopy
... of multivariate statistical analysis (MSA) emerged in the form of correspondence analysis [11] ...Correspondence Analysis (CA) is based on chi-square distances [13]-[15], which are ...
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Multivariate Statistical Analysis of Phyllite Samples Based on Chemical (XRF) and Mineralogical Data by XRD
... a multivariate statistical analysis concerning the chemical and phase composition, as a characterization purpose, carried out with 52 rock phyllite samples selected from the provinces of Almería and ...
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Multivariate Statistical Analysis for the Assessment of Hydrogeochemistry of Groundwater in Upper Kambo Watershed (Douala Cameroon)
... Many statistical methods are developed to facilitate the treatment of a certain volume of ...study, multivariate statistical analysis including principal components analysis (PCA) and ...
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Water Quality Analysis by Multivariate Statistical Analysis in Gazipur Industrial Area, Bangladesh
... Multivariate statistical analysis was determined by SPSS (Statistical Package for Social Science) and Microsoft ...Excel.Cluster analysis, a multivariate statistical ...
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Comparison of multivariate statistical analysis methods
... the statistical analysis ...component analysis and factor analysis. Then four discriminant analysis methods are compared in ...suitable statistical analysis ...
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Application of multivariate statistical analysis in the assessment of water quality of vlora bay, albania
... different multivariate statistical techniques, Principal Component (PCA), helps in the interpretation of complex data matrices to better understand the water quality and ecological status of the studied ...
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Classification of financial ratios of public sector banks in india using multivariate statistical analysis
... factor analysis, BTOII, NIITOTA, BTOTA, OPTOTA, OINCTTIN and PCTOTA had greater value than other components and it formed the first factor, (Factor ...the multivariate discriminant analysis for the ...
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Gini s ideas: new perspectives for modern multivariate statistical analysis
... Recently larger and larger data sets, also as far as the number of observed vari- ables is concerned, have become available thus requiring the development of new techniques also capable to face the so called curse of ...
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Evaluation of water quality using heavy metal index and multivariate statistical analysis in Lorestan province, Iran
... study, statistical studies (correlation coefficient, factor analysis and cluster analysis) were employed to determine the probable origin of the area’s ...
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Structure Sorting of Multiple Macromolecular States in Heterogeneous Cryo EM Samples by 3D Multivariate Statistical Analysis
... dynamics analysis of large macromolecular ...the analysis of virus structures for which starting structures can in principle be determined by using a single or very few molecular views ...
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TyPTex: Inductive Typological Text Classification by Multivariate Statistical Analysis for NLP Systems Tuning/Evaluation
... on multivariate analysis of linguistic ...and statistical tools and on the other hand retracing the results of these tools through the annotation layers back to the primary textual ...
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Multivariate statistical analysis for damage and delamination in composite structures
... Component Analysis with the variables analysed being lagged versions of a single time series variable ...vibration analysis and health monitoring which applies Multichannel Singular Spectrum Analysis ...
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Comparing Statistical Similarity Measures for Stylistic Multivariate Analysis
... by multivariate statistical analysis techniques typically applied in computational stylistic ...numbers. Multivariate sta- tistical techniques are then applied to the data to look for ...
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On model selection in data envelopment analysis: a multivariate statistical approach
... of multivariate statistical analysis to visualize important aspects of the models ...tools, statistical analysis, and the exercise of ...
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Robustness and multivariate analysis
... The majority of algorithms used to construct principal curves, introduced by Hastie and Stuetzle (1989), work by applying principal component analysis it- eratively. At each iteration, only points that are close ...
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Statistical Analysis of Trends of Malaria Diagnosis and Patient Demographics: A Multivariate Study of Clinic Data in Ghana
... Yet another study sought to examine the YF vaccination coverage among French travelers who were suspected to be infected by YF virus while in Senegal. The study also sought to determine the factors that had association ...
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Introduction to Multivariate Analysis
... Overview Introductions Course Overview Data Organization Descriptive Statistics Graphical Techniques • Bivariate Scatterplots • Trivariate Scatterplots • Stars • Chernoff Faces • Dendrog[r] ...
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Detecting falsified financial statements: a comparative study using multicriteria analysis and multivariate statistical techniques
... conducted analysis suggests that there is a strong potential in detecting FFS through the examination of publicly available financial ...well-established statistical classification procedures, support ...
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Application of Multivariate Statistical Methods in the Analysis of Czech Population Life Quality with Attention to Regional Differentiation
... Selection of indicators and consequent reduction of these was based on correlation analysis and principal component analysis. Correlation analysis used the Spearman rank correlation coeffi cient. In ...
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Simple components, correlated components and an application of statistical shape analysis to consumer and other multivariate data
... The analysis was performed using the shape representation based on the Euclidean dis- tance matrix (EDM). The resulting covariance matrix was standardized by scaling so that the variances were unity. The resulting ...
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