correlated: Calculate correlation structure

In tiger: TIme series of Grouped ERrors

Description

Calculate the correlation structure between multiple performance measures

Usage

correlated(result, limit = 0.85, plot.scatter = FALSE, keep = NA)
correl(measures, limit = 0.85, plot.scatter = FALSE, keep = NA)

Arguments

result	object returned from tiger
measures	data.frame for which to determine correlation structure
limit	Limit for absolute correlation, above which data is considered to be correlated
plot.scatter	Boolean, indicating whether to show pairwise plots for correlated measures
keep	Vector with names of measures that must not be excluded because of correlation with other measures

Value

correl returns:

pairs	Matrix with indices of pairwise correlated measures
pairs.by.name	Matrix with measure names of pairwise correlated measures
possible.exclusion	List indicating which measures might be removed to end up with no strongly correlated measures. The list also indicates, which measure is correlated to the removed measures
to.drop	List of indices for measures to drop (according to previous list)
to.drop.by.name	List of measure names (of the previous list)

correlated returns a list of two correl results, one for the original performance measures and one for the transformed measures from a result from tiger.

Author(s)

Dominik Reusser

See Also

This method helps to reduce the amount of data to be analyzed from an evaluation using tiger

Examples

data(tiger.example)
correlated <- correlated(tiger.single, keep=c("CE","RMSE" ))

tiger documentation built on May 2, 2019, 2:22 a.m.