compute.sim: Similarity
In FSMUMI: Imputation of Time Series Based on Fuzzy Logic

Description Usage Arguments Details Author(s) Examples

Compute the percentage of similarity of two univariate signals Y (imputed values) and X (true values).

1	compute.sim(Y, X)

`Y`	vector of imputed values
`X`	vector of true values

This function returns the value of similarity of two v univariate signals. A higher similarity (Similarity \in [0, 1]) highlights a more accurate method for completing missing values. Y and X must have the same length, otherwise an error will be displayed. Input vectors do not contains NA, if not it a warning will be diplayed.

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

data(dataFSMUMI)
X <- dataFSMUMI[, 1] ; Y <- dataFSMUMI[, 2]
compute.sim(Y,X)

# By definition, if true values is a constant vector
# and one or more imputed values are equal to the true values,
# similarity = 1.
X <- rep(5, 100)
Y <- X
compute.sim(Y,X)