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    Home >> Support >> Documentation >> NumXL >> Reference Manual >> Factor Analysis >> Principal Component Analysis

    Principal Component Analysis

    Principal component analysis (PCAi) is a mathematical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.

    Examples

    References

    • Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0-691-04289-6
    • Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740
    • Jolliffe, I.T. (2002). Principal Component Analysis, second edition (Springer).

    Related Links

    • Wikipedia - Principal component analysis
    • Wikipedia - Principal component regression
    • PCA_COMP
    • PCA_VAR
    • PCR_ANOVA
    • PCR_FITTED
    • PCR_FORE
    • PCR_GOF
    • PCR_PARAM
    • PCR_PRFTest
    • PCR_STEPWISE
    ‹ MLR_STEPWISEupPCA_COMP ›

    Tips & Hints

    • Principal Component Analysis (PCA)

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