compute.sim {DTWBI} | R Documentation |

## Similarity

### Description

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

### Usage

```
compute.sim(Y, X)
```

### Arguments

`Y` |
vector of imputed values |

`X` |
vector of true values |

### Details

This function returns the value of similarity of two vectors corresponding to univariate signals.
A higher similarity (`Similarity \in [0, 1]`

) highlights a more accurate method for completing missing values in univariate datasets.
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 excluded with a warning diplayed.

### Author(s)

Camille Dezecache, Hong T. T. Phan, Emilie Poisson-Caillault

### Examples

```
data(dataDTWBI)
X <- dataDTWBI[, 1] ; Y <- dataDTWBI[, 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(2, 10)
Y <- X
compute.sim(Y,X)
```

[Package

*DTWBI*version 1.1 Index]