Principal components analysis
Top PDF Principal components analysis:
Recursive Principal Components Analysis Using Eigenvector Matrix Perturbation
... Principal components analysis is an important and well-studied subject in statistics and signal processing. The literature has an abundance of algorithms for solving this problem, where most of these ...
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Application of Surface Water Quality Classification Models Using Principal Components Analysis and Cluster Analysis
... of principal components analysis (PCA), Fuzzy C -Means (FCM) and K -means algorithm for clustering analysis, this study attempted to determine the major dominant factors responsible for the ...
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A Likelihood-Free Estimator of Population Structure Bridging Admixture Models and Principal Components Analysis
... admixture components, and then search for a model within this subspace that is consistent with the admixture model’s natural probabilistic ...introduced principal components analysis method ...
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Principal Components Analysis a method Useful in Identification of Clusters of Variables
... the analysis the variance accounted by resultant 6 components was ...the principal components analysis. Thus the final analysis was carried out by removing attitudes At1 and ...
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Correctness results for on-line robust principal components analysis
... Another interpretation of the original problem is as a robust principal components analysis (PCA) problem. Given a matrix of data, the goal of PCA is to compute a small number or orthogonal ...
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COPD phenotype description using principal components analysis
... factor analysis [14,15] is a hypothesis generating method that identifies groups of associated parameters into factors that are responsible for disease ...[16]. Principal components analysis ...
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Kernel Principal Components Analysis with Extreme Learning Machines for Wind Speed Prediction
... Abstract—Nowadays, wind power and precise forecasting are of great importance for the development of modern electrical grids. In this paper we propose a prediction system for time series based on Kernel Principal ...
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Permutation validated principal components analysis of microarray data
... the analysis, the data must be pre- processed by background subtraction, computation of ratios and array-wise ...[8], principal components analysis (PCA) [9-13] and correspondence ...
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Principal Components Analysis of Acacia burkei and A. nigrescens in Natal
... Four principal component analyses were carried out to study the perplexing relations within Acacia burkei ...of principal components analysis was most useful in this ...
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A Comparative Study of Various Inclusive Indices and the Index Constructed by the Principal Components Analysis
... The Principal Components Analysis (PCA) is perhaps the most-used method to obtain weights intrinsically. The PCA determines weights of different variables such that the sum of the squared ...
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Application of Principal Components Analysis Results in Visual Network Analysis
... of principal components analysis in a roleof a preprocessor of the source data and its role in visual network analysis ...that principal components analysis could be used ...
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Functional Principal Components Analysis with Survey Data
... We propose in this work to give estimators of the functional principal components analysis when the curves are collected with survey sampling strategies. Let us note that Skinner et al. (1986) have ...
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A comparison of dietary patterns derived by cluster and principal components analysis in a UK cohort of children
... Some studies (Costacou et al, 2003; Kant et al, 2004; Newby et al, 2004; Bamia et al, 2005; Crozier et al, 2006; Reedy et al, 2010) have directly compared the dietary patterns obtained via PCA and cluster ...
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Fault Classification and Localization in Power Systems Using Fault Signatures and Principal Components Analysis
... fault analysis is to provide enough information to understand the reasons that lead to an interruption and to, as soon as possible, restore the handover of power, and perhaps minimize future occur- rences if ...
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Principal Components Analysis with Spline Optimal Transformations for Continuous Data
... NLPCA’s most known approaches among researchers deal- ing with continuous variables do not include the state-of- the-art to perform NLPCA for ordinal and nominal data, CATegorical PCA (CATPCA). We refer to a continuous ...
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A principal components analysis of the UK term structure and the influence of fiscal policy
... Dynamic Equation for Inflation Dynamic Equation for the Change in the Deviation of GDP frorn its Trend Dynamic Equation for the Change in Interest Paymentsas a Ratio of Total Gilts Outst[r] ...
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Specificity of the Culture of Governance in the Mediterranean Arab Countries: A Principal Components Analysis
... The principal component analysis allowed us to identify the main discriminating factors, distinguishing countries by two dominant components: (i) the degree of formalization and depersonalization of ...
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Principal components analysis based control of a multi-dof underactuated prosthetic hand
... An analysis on how tensions vary in the three considered prototypi- cal cases, using the automatic ideal, noisy and “ right- angle ” trajectories, has been performed and is here ...
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Dietary patterns obtained through principal components analysis: The effect of input variable quantification
... Puddings Dairy puddings Cakes Chocolate Sweets candy Sugar Sweet spreads Biscuits cookies Crackers and crispbreads Crisps potato chips Low energy density sauce High energy density sauce [r] ...
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The ‘not-so-strange’ body in the mirror: A principal components analysis of direct and mirror self-observation : A principal components analysis of direct and mirror self-observation
... these components and pre-existing tendencies for appearance anxiety, body dysmorphic-type beliefs, dissociative symptomatology, self-objectification and delusion ideation further supported the similarity between ...
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