Correlation
corr.Rd
Compute the correlation of observed and predicted data.
Arguments
- obs
A vector, data.frame or data.table with observed data.
- pred
A vector, data.frame or data.table with predicted (model) data.
- ...
Optional parameters sent to
cor
.
Details
This is a convenience function to the stats::cor()
function.
See cor
documentation for further details.
Optional parameters are sent to cor
. The most important are:
use
an optional character giving a method for computing covariances in the presence of missing values. This must be one of the strings "everything", "all.obs", "complete.obs", "na.or.complete", or "pairwise.complete.obs". Seecor
documentation for further details.method
a character string indicating which correlation coefficient to be computed. One of "pearson" (default), "kendall" or "spearman".
Examples
# Generate two random temperature series in the range of 20, 30 (for testing purpose):
x <- runif(n = 10, min = 20, max = 30)
y <- runif(n = 10, min = 20, max = 30)
corr(x, y)
#> [1] 0.542282
if (FALSE) {
# temperature is a data.frame is obs and pred columns:
corr(temperature$obs, temperature$pred, use = "complete.obs")
# temperature is a data.table with obs and pred columns:
temperature[, .(corr(obs, pred, use = "complete.obs")), by = cod_brace]
}