n = number of rows
p = number of variables
X = n by p matrix of data values
When you select the Wide method, the data are standardized. To standardize a value, subtract its mean and divide by its standard deviation. Denote the n by p matrix of standardized data values by Xs. Then the covariance matrix of the standardized data is the correlation matrix of X and it is given as follows:
Using the singular value decomposition, Xs is written as UDiag(Λ)V’. This representation is used to obtain the eigenvectors and eigenvalues of Xs’Xs. The principal components, or scores, are given by . For additional background information, see Wide Linear Methods and the Singular Value Decomposition in Statistical Details.
Sparse
Consider the same notation and standardization of X that is described in Wide. The correlation matrix of X is represented by the covariance matrix of Xs:

Help created on 9/19/2017