Principal Component Analysis: Methods, Applications and Technology


Virginia Gray (Editor)

Series: Mathematics Research Developments
BISAC: MAT034000

This book provides new research on principal component analysis (PCA). Chapter One introduces typical PCA applications of transcriptomic, proteomic and metabolomic data. Chapter Two studies the factor analysis of an outcome measurement survey for science, technology and society. Chapter Three examines the application of PCA to performance enhancement of hyperspectral radiative transfer computations. (Imprint: Novinka)

Table of Contents

Table of Contents


Chapter 1. The Principal Component Analysis of Omics Data
Hiroyuki Yamamoto (Human Metabolome Technologies, Inc., Mizukami, Kakuganji, Tsuruoka, Yamagata, Japan)

Chapter 2. A Factor Analysis of an Outcome Measurement Survey for Science, Technology and Society: A Course of General Education Based on PCA
Tzu-Yi Pai, Yi-Ti Tung, Ming-Ray Lin, Su-Hwa Lin, Lung-Yi Chan and Chia-Fu Lin (Master Program of Environmental Education and Management, Department of Science Education and Application, National Taichung University of Education, Taichung, Taiwan, ROC, and others)

Chapter 3. The Application of Principal Component Analysis (PCA) to Performance Enhancement of Hyperspectral Radiative Transfer Computations
Robert Spurr, Vijay Natraj, Pushkar Kopparla and Matt Christi (RT Solutions Inc., Cambridge, MA, USA, and others)



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