Resumé
Two contrasting multivariate data sets (a process data series vs. a 1-D geochemical soil profile) are analyzed to illustrate the benefits of using bilinear projection scores for variographic characterization instead of using individual variables. By using absolute variograms on a validated number of component scores, it is possible to make a combined multivariate chemometrics-variogram characterization of heterogeneous processes and materials as well as 1-D transects, no longer restricted to a one-variable-at-a-time framework. The usefulness and information on variographic modeling based on scores are illustrated. A new test for randomness of a variogram is presented.
Originalsprog | Engelsk |
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Sider (fra-til) | 395-410 |
Antal sider | 16 |
Tidsskrift | Journal of Chemometrics |
Vol/bind | 28 |
Udgave nummer | 5 |
DOI | |
Status | Udgivet - maj 2014 |
Programområde
- Programområde 3: Energiressourcer