This book provides a self-contained and unified treatment of matrix differential calculus, aimed at econometricians and statisticians. It can be used as a textbook for senior undergraduate or graduate courses on the subject, and will also be a valuable source for professional econometricians and statisticians who want to learn and apply these important techniques. The authors base their approach on differentials rather than derivatives, and they show that the use of differentials is elegant, easy and considerably more useful in applications. No specialist knowledge of matrix algebra or calculus is required, since the basics of matrix algebra are covered in the first three chapters with a thorough treatment of multivariable calculus provided in Chapters Four to Seven. Exercises are included in each chapter, and many examples which illustrate applications of the theory are considered in detail.
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" the best book to learn matrix and related ideas statisticians, econometricians, computer scientists, engineers, and psychometricians will find this extremely useful." ( Journal of Statistical Computation and Simulation, March 2006)
"a most welcome revision" (Computational Statistics & Data Analysis, 28 August 2001)
"...deals rigorously with many of the problems that have bedevilled the subject up to the present time..."
Stephen Pollock, Econometric Theory
"I continued to be pleasantly surprised by the variety and usefulness of its contents"
Isabella Verdinelli, Journal of the American Statistical Association
Continuing the success of their first edition, Magnus and Neudecker present an exhaustive and self–contained revised text on matrix theory and matrix differential calculus. Matrix calculus has become an essential tool for quantitative methods in a large number of applications, ranging from social and behavioural sciences to econometrics. While the structure and successful elements of the first edition remain, this revised and updated edition contains many new examples and exercises.
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