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Home > Mathematics and Science Textbooks > Mathematics > Probability and statistics > Matrix Algebra: Theory, Computations and Applications in Statistics(Springer Texts in Statistics)
Matrix Algebra: Theory, Computations and Applications in Statistics(Springer Texts in Statistics)

Matrix Algebra: Theory, Computations and Applications in Statistics(Springer Texts in Statistics)


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About the Book

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



    Table of Contents:
    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.

    About the Author :

    James E. Gentle is University Professor Emeritus at George Mason University. He is a Fellow of the American Statistical Association (ASA) and of the American Association for the Advancement of Science. He has held several national offices in the ASA and has served as 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, Computational Statistics, and Statistical Analysis of Financial Data. He is co-editor-in-chief of Wiley Interdisciplinary Reviews: Computational Statistics.


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    Product Details
    • ISBN-13: 9783031421433
    • Publisher: Springer International Publishing AG
    • Publisher Imprint: Springer International Publishing AG
    • Edition: Revised edition
    • Language: English
    • Returnable: Y
    • Series Title: Springer Texts in Statistics
    • Width: 178 mm
    • ISBN-10: 3031421434
    • Publisher Date: 07 Mar 2024
    • Binding: Hardback
    • Height: 254 mm
    • No of Pages: 693
    • Returnable: Y
    • Sub Title: Theory, Computations and Applications in Statistics


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