compute.nmae {DTWBI} | R Documentation |
Estimates the Normalized Mean Absolute Error of two univariate signals Y (imputed values) and X (true values).
compute.nmae(Y, X)
Y |
vector of imputed values |
X |
vector of true values |
This function returns the value of NMAE of two vectors corresponding to univariate signals.
A lower NMAE (NMAE \in [0, \inf]
) value indicates a better performance method for the imputation task.
Both vectors Y and X must be of equal length, on the contrary an error will be displayed.
In both input vectors, eventual NA will be exluded with a warning diplayed.
Camille Dezecache, Hong T. T. Phan, Emilie Poisson-Caillault
data(dataDTWBI)
X <- dataDTWBI[, 1] ; Y <- dataDTWBI[, 2]
compute.nmae(Y,X)
# If true values is a constant vector, NMAE = Inf.
# A warning is displayed and MAE is estimated instead of NMAE,
# unless true and imputed values are equal. In this case,
# by definition, NMAE = 0.
X <- rep(0, 10)
Y <- runif(10)
compute.nmae(Y,X) # MAE computed
Y <- X
compute.nmae(Y,X) # By definition, NMAE = 0