Principal Component Analysis

This book describes and discusses the use of principal component analysis (PCA) for different types of problems in a variety of disciplines, including engineering, technology, economics, and more.

This volume on principal component analysis (PCA) explores the core analyses and case studies within this field, incorporating the latest advancements. The book emphasizes the integration of PCA with other algorithms and methodologies, highlighting the enhancements achieved through combined approaches.

This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component analysis methods (PCMs) in R.

Exploratory and objective data analysis methods applied to the physical, engineering, and biological sciences. Brief review of statistical methods and their computational implementation for studying time series analysis, spectral analysis, filtering methods, principal component analysis, orthogonal mode decomposition, and image processing and compression.