Linear Models and Regression With R: An Integrated Approach

Debasis Sengupta, Sreenivasa Rao Jammalamadaka

ISBN 10: 0000988847 / ISBN 13: 9780000988843

Published by World Scientific, 2020

About this Item

Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Seller Inventory # ABNR-172433

Bibliographic Details

• Title: Linear Models and Regression With R: An Integrated Approach
• Publisher: World Scientific
• Publication Date: 2020
• Language: English
• ISBN 10: 0000988847
• ISBN 13: 9780000988843
• Binding: Soft cover
• Edition: International Edition
• Condition: New

About this title

Synopsis

Starting with the basic linear model where the design and covariance matrices are of full rank, this book demonstrates how the same statistical ideas can be used to explore the more general linear model with rank-deficient design and/or covariance matrices. The unified treatment presented here provides a clearer understanding of the general linear model from a statistical perspective, thus avoiding the complex matrix-algebraic arguments that are often used in the rank-deficient case. Elegant geometric arguments are used as needed. The book has a very broad coverage, from illustrative practical examples in Regression and Analysis of Variance alongside their implementation using R, to providing comprehensive theory of the general linear model with 181 worked-out examples, 227 exercises with solutions, 152 exercises without solutions (so that they may be used as assignments in a course), and 320 up-to-date references. This completely updated and new edition of Linear An Integrated Approach includes features such Applications with data sets, and their implementation in R, Comprehensive coverage of regression diagnostics and model building, Coverage of other special topics such as collinearity, stochastic and inequality constraints, misspecified models, etc.