Survey of Key Descriptive References for Chemometric Methods Used for Spectroscopy: Part II

被引：0
作者：
Workman, Jerome, Jr. [1 ,2 ,3 ,4 ,5 ]
Mark, Howard [1 ,6 ]
机构：
[1] Spectroscopy, Editorial Advisory Board, Iselin, NJ 08830 USA
[2] LCGC, Cranbury, NJ USA
[3] US Natl Univ, La Jolla, CA USA
[4] Unity Sci, Res & Engn, Brookfield, CT USA
[5] Proc Sensors Corp, Brookfield, CT USA
[6] Mark Elect, Consulting Serv, Suffern, NY 10901 USA
来源：
SPECTROSCOPY | 2021年 / 36卷 / 10期
关键词：
PARTIAL LEAST-SQUARES; PRINCIPAL COMPONENTS REGRESSION; TRANSFORM INFRARED-SPECTROSCOPY; LOCALLY WEIGHTED REGRESSION; MULTIPLE LINEAR-REGRESSION; SUPPORT VECTOR MACHINES; ARTIFICIAL NEURAL-NETWORKS; MULTIVARIATE-ANALYSIS; QUANTITATIVE-ANALYSIS; CLASSIFICATION;
D O I：
10.56530/spectroscopy.pj5166a9
中图分类号：
O433 [光谱学];
学科分类号：
0703 ; 070302 ;
摘要：
This article is the second in a series that lists four key explanatory or tutorial references for each of the 29 chemometric methods previously described. The references selected are particularly helpful to explain the use of each method for spectroscopic data. Also included are common computer software platforms used for chemometrics.
引用
收藏
页码：16 / 19
页数：4
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