similarity_to_dissimilarity {bioregion} | R Documentation |

## Convert similarity metrics to dissimilarity metrics

### Description

This function converts a `data.frame`

of similarity metrics between sites to
dissimilarity metrics (beta diversity).

### Usage

```
similarity_to_dissimilarity(similarity, include_formula = TRUE)
```

### Arguments

`similarity` |
the output object from |

`include_formula` |
a |

### Value

A `data.frame`

with additional class
`bioregion.pairwise.metric`

, providing dissimilarity
metric(s) between each pair of sites based on a similarity object.

### Note

The behavior of this function changes depending on column names. Columns
`Site1`

and `Site2`

are copied identically. If there are columns called
`a`

, `b`

, `c`

, `A`

, `B`

, `C`

they will also be copied identically. If there
are columns based on your own formula (argument `formula`

in `similarity()`

)
or not in the original list of similarity metrics (argument `metrics`

in
`similarity()`

) and if the argument `include_formula`

is set to `FALSE`

,
they will also be copied identically. Otherwise there are going to be
converted like they other columns (default behavior).

If a column is called `Euclidean`

, its distance will be calculated based
on the following formula:

\(Euclidean distance = (1 - Euclidean similarity) / Euclidean similarity\)

Otherwise, all other columns will be transformed into dissimilarity with the following formula:

\(dissimilarity = 1 - similarity\)

### Author(s)

Maxime Lenormand (maxime.lenormand@inrae.fr), Boris Leroy (leroy.boris@gmail.com) and Pierre Denelle (pierre.denelle@gmail.com)

### See Also

`dissimilarity_to_similarity()`

`similarity()`

`dissimilarity()`

### Examples

```
comat <- matrix(sample(0:1000, size = 50, replace = TRUE,
prob = 1 / 1:1001), 5, 10)
rownames(comat) <- paste0("Site", 1:5)
colnames(comat) <- paste0("Species", 1:10)
simil <- similarity(comat, metric = "all")
simil
dissimilarity <- similarity_to_dissimilarity(simil)
dissimilarity
```

*bioregion*version 1.1.1 Index]