Examples of using Component analysis in English and their translations into Portuguese
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Colloquial
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Official
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Medicine
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
Chemometric methods of hierarchy analysis(ha) and principal component analysis(pca) were applied to chromatograms(hplc)
multivariate statistical analysis, principal component analysis(pca) and cluster analysis ca.
Principal component analysis of metabolites involved in energy homeostasis on flies carrying OreR
The interval principal component analysis(ipca) is used
Data were analyzed by means of describing data, main component analysis, factor analysis
multivariate statistical analysis main component analysis.
principal component analysis with a varimax rotation
Multivariate techniques were used: principal component analysis and cluster analysis. .
and independent component analysis.
Principal Component Analysis was the extraction method used and Varimax rotation was employed.
Component analysis indicated that sugarcane burning was the main source of PM 2.5 60%, Soil dust was responsible for 14%, while factories and combustion, 12% each.
Principal component analysis was used in order to reduce the dimensionality of the data collected,
After, it used multivariate statistical with factorial analysis by principal component analysis(pca) and its use has confirmatory character,
LLAEP component analysis was performed by the first author
Exploratory factor analysis was carried out through Principal Component Analysis, with recourse to orthogonal rotation according to the Varimax method.
Exploratory factor analysis was performed through Principal Component Analysis using orthogonal rotation according to the Varimax method.
the lsca is compared with principal component analysis(pca) for detecting local sources under gaussian white noise.
Factorial validity was determined by principal component analysis which results in factorial loads that indicate how much each item is associated with each subscale.
principal variation component analysis PCA was used in this set of data Figure 1.
Principal component analysis was used as the extraction method. Varimax orthogonal rotation was used to determine the relevance of the variables to the identified components. .