Abstract
An interactive minicomputer program in BASIC is presented for implementing abstract factor analysis (AFA) on small core systems. The program converts an original data matrix P = EC into a dispersion (covariance) matrix A = PPT (or PTP), performs a complete eigenanalysis, and determines the correct number of factors spanning the original data space. The criteria for choosing the significant components are based on a combination of (i) size of eigenvalues; (ii) Exner and Malinowski indicator functions; and (iii) minimum number of eigenvectors needed to reproduce the original data matrix within some measure of experimental error. Provision is made for plotting graphical features of the algorithm along with printing options for intermediate results. It is shown that although no unequivocal indicators of the number of factors to be retained can be conceived of, a sound use of the program compounded with chemical expertise and judgment may lead to a satisfactory compression of the original data space.
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