Let X Є pxn denote a zero mean observation matrix matrix of obser- vations, P be a pxp orthogonal matrix, and Y = PTX. (a) Show that if C is the covariance matrix of X then PTCP is the co- variance matrix of Y = PT CP. (b) It can be verified that tr (FG) = tr (GF) for any two n x n matrices F and G. Use this fact to show that the total variance of the data in Y is equal to the total variance of the data in X.

MATLAB: An Introduction with Applications
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Let X Є pxn denote a zero mean observation matrix matrix of obser-
vations, P be a pxp orthogonal matrix, and Y = PTX.
(a) Show that if C is the covariance matrix of X then PTCP is the co-
variance matrix of Y = PT CP.
(b) It can be verified that tr (FG) = tr (GF) for any two n x n matrices
F and G. Use this fact to show that the total variance of the data in Y
is equal to the total variance of the data in X.
Transcribed Image Text:Let X Є pxn denote a zero mean observation matrix matrix of obser- vations, P be a pxp orthogonal matrix, and Y = PTX. (a) Show that if C is the covariance matrix of X then PTCP is the co- variance matrix of Y = PT CP. (b) It can be verified that tr (FG) = tr (GF) for any two n x n matrices F and G. Use this fact to show that the total variance of the data in Y is equal to the total variance of the data in X.
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