Chemometric exploration of sea water chemical component data sets with missing elements

Author:

Smoliński Adam1,Falkowska Lucyna2,Pryputniewicz Dorota2

Affiliation:

1. Central Mining Institute , Pl. Gwarkow 1, 40-166 Katowice , Poland 1

2. Institute of Oceanography , University of Gdańsk , Al. Piłsudskiego 46, 81-378 Gdynia , Poland 2

Abstract

Abstract The results of the application of chemometric methods, such as principal component analysis (PCA) and its generalization for N-way data, the Tucker3 model, for the analysis of an environmental data set are presented. The analyzed data consists of concentration values of chemical compounds of organic matter, and their transformed products, in a short-term study of a sea water column measured at the Gdańsk Deep (φ = 55°1'N, λ = 19°10'E). The main goal of this paper is to present improved approaches for exploration of data sets with missing elements, based on the expectation-maximization (EM) algorithm. The most common methods for dealing with missing data, generally consisting of setting the missing elements to zero or to mean values of the measured data, are often unacceptable as they destroy data correlations or influence interpretation of relationships between objects and variables. The EM algorithm may be built into different computational procedures used for exploratory analysis (i.e. EM/PCA or EM/TUCKER3).

Publisher

Walter de Gruyter GmbH

Subject

Oceanography

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3