as.pca: Coerce input to a 'pca' object

In metno/esd: Climate analysis and empirical-statistical downscaling (ESD) package for monthly and daily data

Coerce input to a pca object

Description

Transform an input object into the esd class pca which is the output of principle component analysis (PCA). PCA decomposes a group of time series (a station object) into a set of spatial patterns (stored as the attribute 'pattern' of the pca object), corresponding time series (the core of the pca object often referred to as principle components), and eigenvalues that represent the relative strength of each spatial pattern. as.pca is an S3 method and will redirect to a fitting function depending on the output. The way in which the transformation is performed depends on the type of input data.

Usage

as.pca(x, verbose = FALSE, ...)

Arguments

x	the input object
verbose	if TRUE print progress
...	other arguments

Value

a pca object

See Also

PCA

metno/esd documentation built on April 24, 2024, 9:19 p.m.