xvErrorMeasures.default: Cross-validation errror measures

In gmGeostats: Geostatistics for Compositional Analysis

Cross-validation errror measures

Description

Compute one or more error measures from cross-validation output

Usage

## Default S3 method:
xvErrorMeasures(x, krigVar, observed, output = "MSDR1", ...)

Arguments

x	a vector containing the predicted values
krigVar	a vector containing the kriging variances
observed	a vector containing the true values
output	which output do you want? a vector of one or several of c("ME","MSE","MSDR","Mahalanobis")
...	extra arguments for generic functionality

Details

"ME" stands for mean error (average of the differences between true values and predicted values), "MSE" stands for mean square error (average of the square differences between true values and predicted values), and "MSDR" for mean squared deviation ratio (average of the square between true values and predicted values each normalized by its kriging variance). These quantities are classically used in evaluating output results of validation exercises of one single variable. For multivariate cases, see xvErrorMeasures.data.frame().

Value

If just some of c("ME","MSE","MSDR") are requested, the output is a named vector with the desired quantities. If only "Mahalanobis" is requested, the output is a vector of Mahalanobis square errors. If you mix up things and ask for "Mahalanobis" and some of the quantities mentioned above, the result will be a named list with the requested quantities.

See Also

Other accuracy functions: accuracy(), mean.accuracy(), plot.accuracy(), precision(), validate(), xvErrorMeasures()

gmGeostats documentation built on April 18, 2023, 5:08 p.m.