This function reorders the estimated states, which can be useful for a comparison to true parameters or the interpretation of states.
reorder_states(x, state_order = "mean")An object of class fHMM_model, in which states are reordered.
An object of class fHMM_model.
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.
dax_model_3t_reordered <- reorder_states(dax_model_3t, state_order = 3:1)
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