APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO THE INTERPRETATION OF RAINWATER COMPOSITIONAL DATA

被引：25

作者：

ZHANG, PX

DUDLEY, N

URE, AM

LITTLEJOHN, D

机构：

[1] Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, G1 1XL, Cathedral Street

来源：

ANALYTICA CHIMICA ACTA | 1992年 / 258卷 / 01期

关键词：

ATOMIC ABSORPTION SPECTROMETRY; PRINCIPAL COMPONENT ANALYSIS; ACID RAIN; CROSS-VALIDATION; FACTOR ANALYSIS; RAINWATER; WATERS;

D O I：

10.1016/0003-2670(92)85192-9

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

Principal component analysis (PCA), based on non-linear iterative partial least squares (NIPALS) coupled with a cross-validation approach, is applied to data obtained from the chemical analysis of rainwater. The correlation between variables is obtained and their sources identified. The classification of samples into groups by PCA is also investigated. The problem of data scaling and the evaluation of methods for assessing the number of significant components in the data are also discussed.

引用

页码：1 / 10

页数：10

共 23 条

[1]

Dillon W. R., 1984, MULTIVARIATE ANAL ME

[2] CROSS-VALIDATORY CHOICE OF THE NUMBER OF COMPONENTS FROM A PRINCIPAL COMPONENT ANALYSIS [J].