an introduction to Principal Component Analysis (PCA)
an introduction to Principal Component Analysis (PCA)
an introduction to Principal Component Analysis (PCA)
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
usage of <strong>PCA</strong>: Probability distribution for sample PCs<br />
If (i) the n observations of in the sample are independent &<br />
(ii)<br />
is drawn from <strong>an</strong> underlying population that<br />
follows a p-variate normal (Gaussi<strong>an</strong>) distribution<br />
with known covari<strong>an</strong>ce matrix<br />
then<br />
where<br />
is the Wishart distribution<br />
else<br />
utilize a bootstrap approximation
Change language