James E. Gentle

Matrix Algebra (eBook, PDF)

Theory, Computations and Applications in Statistics

• Format: PDF

Produktbeschreibung

Comprehensive coverage of matrix algebra for data science and statistical theory

Over 100 pages of additional material and 30 extra exercises in the new edition

Even clearer text and more comprehensive coverage

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 648
• Erscheinungstermin: 12. Oktober 2017
• Englisch
• ISBN-13: 9783319648675
• Artikelnr.: 53060399

Autorenporträt

¿James E. Gentle, PhD, is University Professor of Computational Statistics at George Mason University. He is a Fellow of the American Statistical Association (ASA) and of the American Association for the Advancement of Science. Professor Gentle has held several national offices in the ASA and has served as editor and associate editor of journals of the ASA as well as for other journals in statistics and computing. He is author of Random Number Generation and Monte Carlo Methods (Springer, 2003) and Computational Statistics (Springer, 2009).

Inhaltsangabe

Part I Linear Algebra.- 1 Basic Vector/Matrix Structure and Notation.- 2 Vectors and Vector Spaces.- 3 Basic Properties of Matrices.- 4 Vector/Matrix Derivatives and Integrals.- 5 Matrix Transformations and Factorizations.- 6 Solution of Linear Systems.- 7 Evaluation of Eigenvalues and Eigenvectors.