This book focuses on projections and singular value decomposition (SVD), essential for multivariate analysis. It provides a comprehensive discussion of generalized inverse matrices and their relation to projections. The text explores these concepts through linear transformations in finite-dimensional vector spaces, benefiting researchers and students in various fields.
