Jan R. Magnus, H. Neudecker

Matrix Differential Calculus with Applications in Statistics and Econometrics

• Broschiertes Buch

Produktbeschreibung

Ein umfassendes Lehrbuch der Matrixdifferentialrechnung für Statistiker und Ökonometriker, in deren Forschungsalltag die Matrixtheorie eine zentrale Rolle spielt. Gegenüber der hervorragend aufgenommenen ersten Auflage haben die Autoren, anerkannte Experten dieses Gebietes, den Text um neue Entwicklungen erweitert; die Beispiele und Übungsaufgaben wurden ebenfalls ergänzt. Matrix calculus has become an essential tool for quantitative methods ina 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.
Part I presents a concise, yet thorough overview of matrix algebra, while the second part develops the theory of differentials. The remaining Parts III to VI combine the theory and application of matrix differential calculus providing the practitioner and researcher with both a quick review and a detailed reference.

Produktdetails

• Verlag: Wiley & Sons
• 2. Aufl.
• Seitenzahl: 432
• Erscheinungstermin: 22. März 1999
• Englisch
• Abmessung: 229mm x 152mm x 25mm
• Gewicht: 680g
• ISBN-13: 9780471986331
• ISBN-10: 047198633X
• Artikelnr.: 09373653

Autorenporträt

Jan R. Magnus is the author of Matrix Differential Calculus with Applications in Statistics and Econometrics, 2nd Edition, published by Wiley. Heinz Neudecker is the author of Matrix Differential Calculus with Applications in Statistics and Econometrics, 2nd Edition, published by Wiley.

Inhaltsangabe

MATRICES: BASIC PROPERTIES OF VECTORS AND MATRICES. Kronecker Products, the
Vec Operator and the Moore-Penrose Inverse. Miscellaneous Matrix Results.
DIFFERENTIALS: THE THEORY: MATHEMATICAL PRELIMINARIES. Differentials and
Differentiability. The Second Differential. Static Optimization.
DIFFERENTIALS: THE PRACTICE: SOME IMPORTANT DIFFERENTIALS. First Order
Differentials and Jacobian Matrices. Second Order Differentials and Hessian
Matrices. INEQUALITIES: INEQUALITIES. THE LINEAR MODEL: STATISTICAL
PRELIMINARIES. The Linear Regression Model. Further Topics in the Linear
Model. APPLICATIONS TO MAXIMUM LIKELIHOOD ESTIMATION: MAXIMUM LIKELIHOOD
ESTIMATION. Simultaneous Equations. Topics in Psychometrics.

Rezensionen

"...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)

"a most welcome revision" (Computational Statistics & Data Analysis, 28 August 2001)