compute.fa2 {DTWBI} | R Documentation |
Estimates the FA2 of two univariate signals Y (imputed values) and X (true values).
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 value of FA2 of two vectors corresponding to univariate signals X (true values) and Y (imputed values).
This FA2 corresponds to the percentage of pairs of values (x_{i}, y_{i}
) satisfying the condition 0,5 <= (Y_{i}/X_{i}) <= 2
.
The closer FA2 is to 1, the more accurate is the imputation model.
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.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)