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Introduction to Multivariate Statistical Analysis in Chemometrics
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下一篇 2008-05-14 01:26:24
Kurt Varmuza
11/15/2008
Presents simple but thorough explanations of
the most important multivariate statistical methods
for analyzing chemical data Illustrates concepts
with graphics
and demo example Offers practical advice on applying methods Provides R software tools to demonstrate
applicationsWhile multivariate statistical methods play a prominent role in chemometrics, they are often misunderstood or unknown among research and laboratory professionals. Using only a short segment of matrix algebra for the description of methods,
Introduction to Multivariate Statistical Analysis in Chemometricspresents simple but thorough explanations of the most important multivariate statistical methods used for analyzing chemical data. This practical guide demonstrates methods using the R software package, considering also robust methods, providing software tools, fully worked out examples, and demo data
from chemistry fields. Various graphical schemes and illustrations supplement the text.
Table of ContentsIntroduction. Multivariate Data. Linear Latent Variables. Principal Component Analysis. Multivariate Exploratory Data Analysis. Multivariate Calibration. Multivariate Classification. Preprocessing. Summary and Outlook.
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