compute.fsd {DTWBI} | R Documentation |
Estimates the Fraction of Standard Deviation (FSD) of two univariate signals Y (imputed values) and X (true values).
compute.fsd(Y, X, verbose = F)
Y |
vector of imputed values |
X |
vector of true values |
verbose |
if TRUE, print advice about the quality of the model |
This function returns the value of FSD of two vectors corresponding to univariate signals. Values of FSD closer to zero indicate 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.fsd(Y,X)
compute.fsd(Y,X, verbose = TRUE)
# By definition, if true and imputed values are equal and constant,
# FSD = 0.
X <- rep(runif(1), 10)
Y <- X
compute.fsd(Y,X)
# However, if true and imputed values are constant but different,
# FSD is not calculable. An error is displayed.
## Not run:
X <- rep(runif(1), 10);Y <- rep(runif(1), 10)
compute.fsd(Y,X)
## End(Not run)