0
Your cart

Your cart is empty

Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software

Buy Now

Matrix-Based Introduction to Multivariate Data Analysis (Hardcover, 2nd ed. 2020) Loot Price: R3,969
Discovery Miles 39 690
Matrix-Based Introduction to Multivariate Data Analysis (Hardcover, 2nd ed. 2020): Kohei Adachi

Matrix-Based Introduction to Multivariate Data Analysis (Hardcover, 2nd ed. 2020)

Kohei Adachi

 (sign in to rate)
Loot Price R3,969 Discovery Miles 39 690 | Repayment Terms: R372 pm x 12*

Bookmark and Share

Expected to ship within 12 - 17 working days

This is the first textbook that allows readers who may be unfamiliar with matrices to understand a variety of multivariate analysis procedures in matrix forms. By explaining which models underlie particular procedures and what objective function is optimized to fit the model to the data, it enables readers to rapidly comprehend multivariate data analysis. Arranged so that readers can intuitively grasp the purposes for which multivariate analysis procedures are used, the book also offers clear explanations of those purposes, with numerical examples preceding the mathematical descriptions. Supporting the modern matrix formulations by highlighting singular value decomposition among theorems in matrix algebra, this book is useful for undergraduate students who have already learned introductory statistics, as well as for graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis. The book begins by explaining fundamental matrix operations and the matrix expressions of elementary statistics. Then, it offers an introduction to popular multivariate procedures, with each chapter featuring increasing advanced levels of matrix algebra. Further the book includes in six chapters on advanced procedures, covering advanced matrix operations and recently proposed multivariate procedures, such as sparse estimation, together with a clear explication of the differences between principal components and factor analyses solutions. In a nutshell, this book allows readers to gain an understanding of the latest developments in multivariate data science.

General

Imprint: Springer Verlag, Singapore
Country of origin: Singapore
Release date: May 2020
First published: 2020
Authors: Kohei Adachi
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 457
Edition: 2nd ed. 2020
ISBN-13: 978-981-15-4102-5
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
Books > Computing & IT > General theory of computing > Mathematical theory of computation
Books > Social sciences > Sociology, social studies > Social research & statistics > General
Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software
LSN: 981-15-4102-7
Barcode: 9789811541025

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!

Partners