euclidean {abdiv} | R Documentation |

These distance and diversity measures are mathematically similar to the Euclidean distance between two vectors.

```
euclidean(x, y)
rms_distance(x, y)
chord(x, y)
hellinger(x, y)
geodesic_metric(x, y)
```

`x` , `y` |
Numeric vectors |

For vectors `x`

and `y`

, the Euclidean distance is defined as

`d(x, y) = \sqrt{\sum_i (x_i - y_i) ^ 2}.`

Relation of `euclidean()`

to other definitions:

Equivalent to R's built-in

`dist()`

function with`method = "euclidean"`

.Equivalent to

`vegdist()`

with`method = "euclidean"`

.Equivalent to the

`euclidean()`

function in`scipy.spatial.distance`

.Equivalent to the

`structeuclidean`

calculator in Mothur, to`speciesprofile`

if`x`

and`y`

are transformed to relative abundance, and to`memeuclidean`

if`x`

and`y`

are transformed to presence/absence.Equivalent to

`D_1`

in Legendre & Legendre.Equivalent to the

*distance between species profiles*,`D_{18}`

in Legendre & Legendre if`x`

and`y`

are transformed to relative abundance.

The *root-mean-square* distance or *average* distance is similar
to Euclidean distance. As the name implies, it is computed as the square
root of the mean of the squared differences between elements of `x`

and `y`

:

`d(x, y) = \sqrt{\frac{1}{n} \sum_i^n (x_i - y_i) ^ 2}.`

Relation of `rms_distance()`

to other definitions:

Equivalent to

`D_2`

in Legendre & Legendre.

The *chord* distance is the Euclidean distance after scaling each
vector by its root sum of squares, `\sqrt{\sum_i x_i^2}`

. The chord
distance between any two vectors ranges from 0 to `\sqrt{2}`

.
Relation of `chord()`

to other definitions:

Equivalent to

`D_3`

in Legendre & Legendre.

The *Hellinger* distance is equal to the chord distance computed after
a square-root transformation. Relation of `hellinger()`

to other
definitions:

Equivalent to

`D_{17}`

in Legendre & Legendre.Equivalent to the

`hellinger`

calculator in Mothur.

The *geodesic metric* is a transformed version of the chord distance.

`d(x, y) = \textrm{arccos} \left(1 - \frac{d_c^2(x, y)}{2} \right),`

where `d_c`

is the chord distance. It gives the length of the arc on a
hypersphere between the vectors, if the vectors are normalized to unit
length. Relation of `geodesic_metric()`

to other definitions:

Equivalent to

`D_4`

in Legendre & Legendre.

The distance between `x`

and `y`

. The chord distance,
Hellinger distance, and geodesic metric are not defined if all elements
of either vector are zero. We return `NaN`

in this case.

```
x <- c(15, 6, 4, 0, 3, 0)
y <- c(10, 2, 0, 1, 1, 0)
euclidean(x, y)
# The "distance between species profiles"
euclidean(x / sum(x), y / sum(y))
rms_distance(x, y)
chord(x, y)
hellinger(x, y)
# Hellinger is chord distance after square root transform
chord(sqrt(x), sqrt(y))
geodesic_metric(x, y)
# No species in common with x
v <- c(0, 0, 0, 5, 0, 5)
chord(v, x)
sqrt(2)
```

[Package *abdiv* version 0.2.0 Index]