This function reorders the estimated states, which can be useful for a comparison to true parameters or the interpretation of states.

## Arguments

- x
An object of class

`fHMM_model`

.- state_order
Either

`"mean"`

, in which case the states are ordered according to the means of the state-dependent distributions,or a vector (or a matrix) which determines the new ordering:

If

`x$data$controls$hierarchy = FALSE`

,`state_order`

must be a vector of length`x$data$controls$states`

with integer values from`1`

to`x$data$controls$states`

. If the old state number`x`

should be the new state number`y`

, put the value`x`

at the position`y`

of`state_order`

. E.g. for a 2-state HMM, specifying`state_order = c(2, 1)`

swaps the states.If

`x$data$controls$hierarchy = TRUE`

,`state_order`

must be a matrix of dimension`x$data$controls$states[1]`

x`x$data$controls$states[2] + 1`

. The first column orders the coarse-scale states with the logic as described above. For each row, the elements from second to last position order the fine-scale states of the coarse-scale state specified by the first element. E.g. for an HHMM with 2 coarse-scale and 2 fine-scale states, specifying`state_order = matrix(c(2, 1, 2, 1, 1, 2), 2, 3)`

swaps the coarse-scale states and the fine-scale states connected to coarse-scale state 2.

## Value

An object of class `fHMM_model`

, in which states are reordered.