CCA: Canonical correlation analysis

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

Canonical correlation analysis

Description

Applies a canonical correlation analysis (CCA) to two data sets. The CCA here can be carried out based on an svd based approach (after Bretherton et al. (1992), J. Clim. Vol 5, p. 541, also documented in Benestad (1998): "Evaluation of Seasonal Forecast Potential for Norwegian Land Temperatures and Precipitation using CCA", DNMI KLIMA Report 23/98 at http://met.no/english/r_and_d_activities/publications/1998.html) or ii) a covariance-eigenvalue approach (after Wilks, 1995, "Statistical methods in the Atmospheric Sciences", Academic Press, p. 401).

Usage

CCA(Y, X, ip = 1:8, verbose = FALSE, ...)

Arguments

Y	An object with climate data: field, eof, pca.
X	Same as Y.
ip	Which EOFs to include in the CCA.
verbose	If TRUE print information about progress.
...	Other arguments.

Details

The analysis can also be applied to either EOFs or fields.

Value

A CCA object: a list containing a.m, b.m, u.k, v.k, and r, describing the Canonical Correlation variates, patterns and correlations. a.m and b.m are the patterns and u.k and v.k the vectors (time evolution).

See Also

predict.cca

Examples

# CCA with two eofs
slp <- slp.NCEP(lat=c(-40,40),anomaly=TRUE)
sst <- sst.NCEP(lat=c(-40,40),anomaly=TRUE)
eof.1 <- EOF(slp, it='Jan')
eof.2 <- EOF(sst, it='Jan')
cca <- CCA(eof.1,eof.2)
plot(cca)

# CCA with PCA and EOF:
## Not run: 
NACD <- station.nacd()
plot(annual(NACD))
map(NACD,FUN="sd")
pca <- PCA(NACD)
plot(pca)
naslp <- slp.NCEP(lon=c(-30,40),lat=c(30,70),anomaly=TRUE)
map(naslp)
eof <- EOF(naslp,it='Jan')
nacca <- CCA(pca,eof)
plot(nacca)
cca.pre <- precit.cca(nacca)

## End(Not run)

metno/esd documentation built on March 9, 2024, 11:21 a.m.