Principal Components and Regression by Singular Value Decomposition on a Small Computer
John C. M. Nash, L. P. Lefkovitch · Journal of the Royal Statistical Society Series C (Applied Statistics) · 1976
A compact program for performing a variety of regression and principal component computations is described. A singular value decomposition of the data matrix is used which permits calculations involving rank deficient data to be handled satisfactorily. The importance of avoiding the calculation of a sum of squares and cross‐products matrix is demonstrated by an example.