What is EOF analysis?
In statistics and signal processing, the method of empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal basis functions which are determined from the data.
How do you interpret EOF analysis results?
You should approach the interpretation of EOFs by looking at both the EOF pattern and the associated time series together. For example, consider an EOF of sea surface temperature. If your EOF has a positive centre and the associated time series is increasing, then you will interpret this centre as a warming signal.
What is the difference between EOF and PCA?
In statistics, EOF analysis is known as Principal Component Analysis (PCA). As such, EOF analysis is sometimes classified as a multivariate statistical technique. However, there is no a priori hypothesis based on some probability distribution and, hence, no statistical test.
What is EOF analysis in statistics?
In statistics, EOF analysis is known as Principal Component Analysis (PCA). As such, EOF analysis is sometimes classified as a multivariate statistical technique. However, there is no a priori hypothesis based on some probability distribution and, hence, no statistical test. Further, EOF analysis is not based on physical principles.
Is classical EOF (PCA) useful for physical systems analysis?
Physical systems are not necessarily orthogonal and if the patterns depend on the region used they may not exist if the the domain changes. Still, even with these short comings, classical EOF (PCA) analysis has proved to be useful.
What are spatial weights in EOF analysis?
Most commonly, the spatial weights are the cos (latitude) or, better for EOF analysis, the sqrt (cos (latitude)). The derived eigenvalues provide a measure of the percent variance explained by each mode. Unfortunately, the eigenvalues are not necessarily distinct due to sampling issues.
Are the principal components of EOFs independent of the pattern?
By construction, the EOF patterns and the principal components are independent. Two factors inhibit physical interpretation of EOFs: (1) the orthogonality constraint and (2) the derived patterns may be domain dependent.