Regression in Engineering and the Applied Sciences - Applications in R

This book presents a broad range of regression models including count regression models, constrained and penalised regression models such as ridge, LASSO, and elasticnet regression that are used in various applied science fields. The author describes the historical development of the least squares principle, simple linear regression, and Polynomial regression. In addition, logistic regression and multiple linear regression are discussed at length. A novel method to estimate the slope of linear regression is presented along with an emphasis on the importance of numeric problems.

List of contents

Types of Regression.- Simple Liner Regression.- Logistic Regression.- Multiple Linear Regression.- Applications of Regression.

About the author

Rajan Chattamvelli, Ph.D., is a Professor in the School of Advanced Sciences at Amrita University, India.  He has published more than 20 research articles in international journals, and his research interests include computational statistics, design of algorithms, parallel computing, data mining, machine learning, blockchain, combinatorics, and big data analytics.

Product details

• Authors: Rajan Chattamvelli
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Release: 02.04.2025, delayed
• EAN: 9783031766718
• ISBN: 978-3-0-3176671-8
• No. of pages: 205
• Illustrations: XVIII, 205 p. 6 illus., 5 illus. in color.
• Series: Synthesis Lectures on Mathematics & Statistics
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Maschinelles Lernen, Statistics, Mathematische und statistische Software, multiple Regression, Statistics and Computing, Statistical Theory and Methods, Statistical Learning, Applied Statistics, Linear Models and Regression, least squares, logistic regression, Ridge Regression, Applications of Regression, Quantile Regression