Principal component analysis: the basic building block of chemometrics

被引:0
|
作者
Cordella, Christophe [1 ]
机构
[1] INA PG AgroParisTech, Inst Sci & Ind Vivant & Environm, GENIAL, Equipe Ingn Analyt Qualite Aliments,INRA,UMR 1145, F-75231 Paris 05, France
来源
ACTUALITE CHIMIQUE | 2010年 / 345期
关键词
Principal component analysis; PCA; chemometrics; data analysis; oil oxidation; Wold; Kowalski; LIPID OXIDATION; PRODUCTS;
D O I
暂无
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Principal component analysis: the basic building block of chemometrics The chemometrics is a discipline involving analysis of data and analytical chemistry. It brings together and develops a set of mathematical tools used to extract information from structured and interpretable chemical data. Many definitions of chemometrics have been proposed, but all have common goal such as finding new tools and new ways to exploit information contained in the data to create knowledge. Some of these tools are more and more applied today to metabolomic and/or metabonomic data. They are designed to show what it would be impossible to do with a univariate data analysis. This contribution aims to present one of the basic techniques of the chemometrics: principal component analysis (PCA). After a historical introduction and the basic principles of the technique, a practical example of use of PCA is developed. The interpretation of results is shown with a pedagogical concern, to better show the power of the tool. The data analyzed in this paper concern a kinetic study of the thermal oxidation of edible oil monitored by proton NMR spectroscopy.
引用
收藏
页码:13 / 18
页数:6
相关论文
共 50 条
  • [31] Segmented principal component transform-principal component analysis
    Barros, AS
    Rutledge, DN
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2005, 78 (1-2) : 125 - 137
  • [32] Block-Wise Two Dimensional Kernel Quaternion Principal Component Analysis
    Chen B.-J.
    Yang J.-H.
    Fan C.-N.
    Su Q.-T.
    Wang D.-C.
    Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 2019, 42 (01): : 53 - 60
  • [33] Degrees of freedom estimation in Principal Component Analysis and Consensus Principal Component Analysis
    Hassani, Sahar
    Martens, Harald
    Qannari, El Mostafa
    Kohler, Achim
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2012, 118 : 246 - 259
  • [34] Principal component analysis of factors influencing pricing decisions of building materials in Ghana
    Obeng-Ahenkora, Nana Kwame
    Danso, Humphrey
    INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT, 2020, 20 (02) : 122 - 129
  • [35] Using principal component and cluster analysis in the heating evaluation of the school building sector
    Gaitani, N.
    Lehmann, C.
    Santamouris, M.
    Mihalakakou, G.
    Patargias, P.
    APPLIED ENERGY, 2010, 87 (06) : 2079 - 2086
  • [36] Principal component analysis for building combined cooling heating and power application potential
    Lin, Bo
    Freihaut, James
    Chen, Zhao
    ASHRAE TRANSACTIONS 2014, VOL 120, PT 2, 2014, 120
  • [37] A principal component analysis of corporate dispositions for sustainable building construction in South Africa
    Emere, Chijioke Emmanuel
    Aigbavboa, Clinton Ohis
    Oguntona, Olusegun Aanuoluwapo
    Ogunbayo, Babatunde Fatai
    FRONTIERS IN BUILT ENVIRONMENT, 2024, 10
  • [38] Principal component analysis and long-term building energy simulation correlation
    Lam, Joseph C.
    Wan, Kevin K. W.
    Wong, S. L.
    Lam, Tony N. T.
    ENERGY CONVERSION AND MANAGEMENT, 2010, 51 (01) : 135 - 139
  • [39] Principal Component Analysis in Building Energy Efficiency Rating System for Apartment Housings
    Jung, Hogun
    Park, Mincho
    Shin, Sungwoo
    ADVANCED CONSTRUCTION TECHNOLOGIES, 2014, 919-921 : 1716 - +
  • [40] Determination of the active principle in a syrup by spectrophotometry and principal component regression analysis -: An advanced undergraduate experiment involving chemometrics
    Ribone, MÉ
    Pagani, AP
    Olivieri, AC
    Goicoechea, HC
    JOURNAL OF CHEMICAL EDUCATION, 2000, 77 (10) : 1330 - 1333