reorder_states: Reorder estimated states

In fHMM: Fitting Hidden Markov Models to Financial Data

Reorder estimated states

Description

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

Usage

reorder_states(x, state_order = "mean")

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.

Examples

dax_model_3t_reordered <- reorder_states(dax_model_3t, state_order = 3:1)

fHMM documentation built on April 3, 2025, 5:49 p.m.