Principal components analysis of FA data
Functional Principal Components Analysis with Survey Data
... Functional Principal Components Analysis (FPCA) thanks to Horvitz-Thompson estimators when the curves are collected with survey sam- pling ...
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Integrating Data Transformation in Principal Components Analysis
... appropriate data transfor- mation and perform principal components analysis/functional principal components ...transformed data matrix has a signal-plus-noise ...
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Permutation validated principal components analysis of microarray data
... backgrounds. The variance in the experimental design was thus quite high. Heterogeneity within the groups was also higher than in the antidepressant experiment, probably because a selective pharmacologic antagonization ...
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A tutorial on Principal Components Analysis
... Wanting to get the original data back is obviously of great concern if you are using the PCA transform for data compression (an example of which to will see in the next section).. This c[r] ...
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Linkage analysis using principal components of gene expression data
... Heather J Cordell, Mariza de Andrade, Marie-Claude Babron, Christopher W ...
Genetic Analysis Workshop 15: Gene Expression Analysis and Approaches to Detecting Multiple Functional Loci
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Principal Components Analysis with Spline Optimal Transformations for Continuous Data
... original data can be viewed as a collection of n points in some high m-dimensional space, the points corresponding to sample individuals and the dimensions to measured variables, and we seek for a suitable low ...
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Principal Components Analysis of Discrete Datasets
... categorical data by some underlying principal ...(or principal components, PC) for this space like what we did for continuous ...these data are generated from some latent variables with ...
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Analysis of principal components of pollution in Baiyangdian
... third principal component is of high correlation coefficient with chorophyll, which reflect the bios character of the lake’s ...the data analysis of site investigation, there is a strong association ...
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Principal components analysis in clinical studies
... multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression ...apply principal components analysis (PCA) over ...
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Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis
... Keywords- cloud masking; spectral analysis; principal components analysis; reflectance; brightness temperature I. I NTRODUCTION Typically, 50% of the Earth’s surface is covered by clouds at ...
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Unsupervised Feature Selection for Principal Components Analysis
... Despite this fact, we noticed that at least a few of the 100 matrices had the following property: the documents clustered well when projected in a low dimensional space spanned by the top few (e.g., four or five) left ...
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Phylogenetic Principal Components Analysis and Geometric Morphometrics
... of data points that arises from shared phylogenetic history for tests whose p-values depend on the assump- tion that data points are independent ...an analysis per se and it serves as a replacement ...
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Nonparametric time dependent principal components analysis.
... The idea behind testing for no time effect using reference bands is simple. If there was no time effect then permuting the values of x i that are associated with t i should lead to similar pc loadings after we have taken ...
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Linkage and association analyses of principal components in expression data
... correlated data presents an interesting set of ...the data providers as showing common linkage to a region of chromosome 14, as well as five other sets suggested by ontological ...Using principal- ...
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City competitiveness; Principal Components Methodology; competitiveness index; Exploratory Spatial Data Analysis.
... STATISTICS ANALYSIS Abstract The objective of this article is to develop a competitiveness index for the 645 cities of the state of São Paulo, Brazil (ICM-SP), using a Principal Components ...
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A principal components method constrained by elementary flux modes: analysis of flux data sets
... flux data using combi- nations of elementary (flux) modes (EM) has been ...flux data, and that PEMs are a faithful representation of active ...the data, it can be con- cluded that the performance did ...
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Application of Principal Components Analysis Results in Visual Network Analysis
... financial data of companies of certain industry in order to measure their activity level authors show that principal components analysis could be used as a preprocessor for further ...network ...
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Principal Components Analysis of Acacia burkei and A. nigrescens in Natal
... the data, even though this taxonomically significant character had been omitted, was to establish whether or not the two species could still be separated by multivariate ...
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Correctness results for on-line robust principal components analysis
... Figure 2.7 illustrates the result we have proven. That is ReProCS takes advantage of the initial subspace estimate and slow subspace change (including the bound on γ new ) to handle the case when the supports of x t are ...
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COPD phenotype description using principal components analysis
... where data was missing [14], so that all of the 92 patients with induced sputum data and 117 patients with Fe NO data could be analysed where possible ...these data could be analysed against ...
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