compute.fa2: FA2
In FSMUMI: Imputation of Time Series Based on Fuzzy Logic

Description Usage Arguments Details Author(s) Examples

Calculate the FA2 between two univariate signals Y (imputed values) and X (true values).

1	compute.fa2(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 FA2 value which corresponds to the percentage of pairs of values (x_{i}, y_{i}) satisfying the condition 0,5 <= (y_{i}/x_{i}) <= 2. FA2 is close to 1, the imputation model is more accurate. 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.

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

data(dataFSMUMI)
X <- dataFSMUMI[, 1] ; Y <- dataFSMUMI[, 2]
compute.fa2(Y,X)
compute.fa2(Y,X, verbose = TRUE)

# By definition, if pairs of true and imputed values are zero,
# FA2 corresponding to this pair of values equals 1.
X[1] <- 0
Y[1] <- 0
compute.fa2(Y,X)