Metric-based principal components:. data uncertainties
| Autor: | W. C. Thacker |
|---|---|
| Rok vydání: | 1996 |
| Předmět: |
Discrete mathematics
Atmospheric Science 010504 meteorology & atmospheric sciences 010505 oceanography Oceanography 01 natural sciences Formalism (philosophy of mathematics) Singular value decomposition Principal component analysis Calculus Applied mathematics Analysis method 0105 earth and related environmental sciences Mathematics |
| Zdroj: | Tellus A; Vol 48, No 4 (1996) |
| ISSN: | 1600-0870 0280-6495 |
| Popis: | Seeking an index characterizing the best-determined mode of variability leads to a natural generalization of principal-component analysis with an explicit metric characterizing the uncertainties of the data. This formalism, which distinguishes between state-space patterns and patterns of coefficients defining principal components, allows the more accurate data to exert a greater influence on the definition of the indices than they do in conventional principal-component analysis; in all other aspects, the new formalism is the same as the old. Within the context of the simple example of Bretherton and collaborators, metric-based principal-component analysis is shown to be capable of finding correlated patterns of variability in two different data sets. DOI: 10.1034/j.1600-0870.1996.t01-3-00007.x |
| Databáze: | OpenAIRE |
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