Includes bibliographical references (pages 321-323) and index.
Matrix defined, deeper understanding using software -- Elementary geomentary geometry and algebra using R -- Vector spaces -- Matrix basics and R software -- Decision applications, payoff matrix -- Determinant and singularity of a square matrix -- The norm, rank and trace of a matrix -- Matrix inverse and solution of linear equations -- Eigenvalues and eigenvectors -- Similar matrices, quadratic and Jordan canonical forms -- Hermitian, normal and positive define matrices -- Kronecker products and singular value decomposition -- Simultaneous reduction and vec stacking -- Vector and matrix differentiation -- Matrix results for statistics -- Generalized inverse and patterned matrices -- Numerical accuracy and QR decomposition.