TERMIUM Plus^®

Fiche 1,  Justifications,  Anglais

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The PCA (principal components analysis) was performed to reduce the 240-intercorrelated weather variables into a small number of linearly independent component variables, which explain much of the variance within the original dataset. Component loadings were calculated, which express the correlation between the original weather variables and the newly formed components. The number of principal components, of which the eigenvalue was greater than one, was retained to calculate component scores. Days with similar meteorological situations tend to exhibit approximately similar component scores.  1, fiche 1, Anglais, - component%20variable

Fiche 1,  Justifications,  Français

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On calcule les corrélations entre les variables initiales et les variables composantes principales [...]  1, fiche 1, Français, - variable%20composante

Fiche 1,  Justifications,  Espagnol