Explaining a presence of groups in analytical data in terms of original variables
Daszykowski, M., Stanimirova, I., Walczak, B., and Coomans, D. (2005) Explaining a presence of groups in analytical data in terms of original variables. Chemometrics and Intelligent Laboratory Systems, 78 (1-2). pp. 19-29.
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This manuscript shows the usefulness of Projection Pursuit (PP) and Multivariate Regression Trees (MRT) for analytical data exploration. Additionally, features of Projection Pursuit and kurtosis as a projection index are presented. The ability of Projection Pursuit to discover groups in the data is compared to classical Principal Component Analysis (PCA). Moreover, it is also demonstrated how the presence of groups in the data can be explained in terms of explanatory variables with the aid of Projection Pursuit and Multivariate Regression Trees. Neither Projection Pursuit nor Multivariate Regression Trees are commonly used for exploring chemical data however, they are able to enrich to a high extent the interpretation.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||analytical data; original variables; exploratory analysis; CART; MRT; projection pursuit; projection index; kurtosis|
|FoR Codes:||01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics @ 50%|
03 CHEMICAL SCIENCES > 0301 Analytical Chemistry > 030106 Quality Assurance, Chemometrics, Traceability and Metrological Chemistry @ 50%
|SEO Codes:||97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 100%|
|Deposited On:||12 Jun 2009 15:08|
|Last Modified:||17 May 2013 00:40|
Last 12 Months: 0
|Citation Counts with External Providers:||Web of Science: 6|
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