Segmentation of movement data. No clustering. Method available for data.frame, move and ltraj object. The algorithm finds for each number of segment the optimal segmentation using a Dynamic Programming approach. The number of segment is then chosen using Lavielle's (2005) procedure based on locating rupture in the penalized likelihood.

```
segmentation(x, ...)
# S3 method for data.frame
segmentation(x, ...)
# S3 method for Move
segmentation(x, ...)
# S3 method for ltraj
segmentation(x, ...)
segmentation_internal(
x,
seg.var,
diag.var,
order.var,
lmin,
Kmax,
scale.variable,
sameSigma = FALSE,
...
)
```

- x
data.frame with observations

- ...
additional parameters given to chooseseg_lavielle

- seg.var
names of the variables used for segmentation (either one or two names).

- diag.var
names of the variables on which statistics are calculated.

- order.var
names of the variable with which states are ordered.

- lmin
minimum length of segments.

- Kmax
maximum number of segments.

- scale.variable
TRUE or FALSE for automatic scaling of variables (reduction and centering)

- sameSigma
does segments have same variance ?

a `segmentation-class`

object