compute.fsd: Fraction of Standard Deviation (FSD)
In FSMUMI: Imputation of Time Series Based on Fuzzy Logic

Description Usage Arguments Details Author(s) Examples

Compute the Fraction of Standard Deviation (FSD) of two univariate signals Y (imputed values) and X (true values).

1	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 FSD value between two univariate signals. FSD value approaches zero means that a better performance method for the imputation task. Y and X must have the same length, conversely an error will be appeared. In both input vectors, NA will be exluded with a warning diplayed.

Thi-Thu-Hong Phan, Andre Bigand, Emilie Poisson-Caillault

data(dataFSMUMI)
X <- dataFSMUMI[, 1] ; Y <- dataFSMUMI[, 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)