Bidimensional and Multidimensional Principal Component Analysis in Long Term Atmospheric Monitoring
Bidimensional and Multidimensional Principal Component Analysis in Long Term Atmospheric Monitoring
About this item
Full title
Author / Creator
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
Atmospheric monitoring produces huge amounts of data. Univariate and bivariate statistics are widely used to investigate variations in the parameters. To summarize information graphs are usually used in the form of histograms or tendency profiles (e.g., variable concentration vs. time), as well as bidimensional plots where two-variable correlations...
Alternative Titles
Full title
Bidimensional and Multidimensional Principal Component Analysis in Long Term Atmospheric Monitoring
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_4f045173f47e4d66ad764677c4575427
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_4f045173f47e4d66ad764677c4575427
Other Identifiers
ISSN
2073-4433
E-ISSN
2073-4433
DOI
10.3390/atmos7120155
