# compute.ed: Euclidean distance (ED) In FSMUMI: Imputation of Time Series Based on Fuzzy Logic

## Description

Compute the Euclidean distance between two vectors having the same length Y and X.

## Usage

 1 compute.ed(Y, X) 

## Arguments

 Y vector of imputed values X vector of true values

## Details

This function returns the Euclidean distance of two vectors corresponding to univariate signals. A lower ED (ED \in [0, \inf]) value indicates that the two vectors are more similar. The both vectors Y and X must be of equal length, on the contrary an error will be displayed. In two input vectors, eventual NA will be exluded with a warning diplayed.

## Author(s)

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

## Examples

 1 2 3 data(dataFSMUMI) X <- dataFSMUMI[, 1] ; Y <- dataFSMUMI[, 2] compute.ed(Y,X) 

FSMUMI documentation built on May 2, 2019, 12:40 p.m.