Ensemble PCA, or Monte Carlo Empirical Orthogonal Functions
pcaEns( bin.list, method = "ppca", weights = NA, pca.type = "corr", gaussianize = TRUE, n.pcs = 8, n.ens = 1000, simulateTrendInNull = FALSE )
A list of binned data, the output of binTs()
What method to use for PCA? pcaMethods::listPcaMethods() for options. "ppca" is default. Other options may not work in GeoChronR.
Vector of weights to apply to timeseries in the bin.list
Correlation ("corr" - default) or Covariance ("cov"), matrix
Map input data to a standard Gaussian distribution? This is only relevant for correlation matrices, covariance matrices will not be gaussianized. (default = TRUE)
number of PCs/EOFs to calculate
how many ensemble members to calculate
Should the null include the trend?