Empirical Orthogonal Teleconnections in R
Create an anomaly RasterStack
Calculate space-time variance of a RasterStack or RasterBrick
Create a weighted covariance matrix
Shorten a RasterStack
Convert degrees to radians
Noise filtering through principal components
Create seasonal anomalies
EOT analysis of a predictor and (optionally) a response RasterStack
Calculate a single EOT
Class EotMode
Class EotStack
Geographic weighting
Calculate weights from latitude
Create lagged RasterStacks
Calculate long-term means from a 'RasterStack'
Names of Eot* objects
Number of modes of an EotStack
Number of EOTs needed for variance explanation
Plot an Eot* object
EOT based spatial prediction
R EMpirical Orthogonal TEleconnections
Subset modes in EotStacks
Write Eot* objects to disk
Empirical orthogonal teleconnections in R. 'remote' is short for 'R(-based) EMpirical Orthogonal TEleconnections'. It implements a collection of functions to facilitate empirical orthogonal teleconnection analysis. Empirical Orthogonal Teleconnections (EOTs) denote a regression based approach to decompose spatio-temporal fields into a set of independent orthogonal patterns. They are quite similar to Empirical Orthogonal Functions (EOFs) with EOTs producing less abstract results. In contrast to EOFs, which are orthogonal in both space and time, EOT analysis produces patterns that are orthogonal in either space or time.