reorder_states

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

Fitting (hierarchical) hidden Markov models to financial data
via maximum likelihood estimation. See Oelschläger, L. and Adam, T.
"Detecting bearish and bullish markets in financial time series using
hierarchical hidden Markov models" (2021, Statistical Modelling)
<doi:10.1177/1471082X211034048> for a reference.

Lennart Oelschläger

fHMM

Fitting Hidden Markov Models to Financial Data

Timo Adam

Rouven Michels

reorder_states function

<dl><dt>x</dt>
<dd>An object of class <code>fHMM_model</code>.</dd>
<dt>state_order</dt>
<dd>A vector or a matrix which determines the new ordering.<ul>
<li>If <code>x$data$controls$hierarchy = FALSE</code>, <code>state_order</code> must
be a vector of length <code>x$data$controls$states</code> with integer
values from <code>1</code> to <code>x$data$controls$states</code>. If the old
state number <code>x</code> should be the new state number <code>y</code>, put
the value <code>x</code> at the position <code>y</code> of <code>state_order</code>.
E.g. for a 2-state HMM, specifying <code>state_order = c(2,1)</code> swaps
the states.</li>
<li>If <code>x$data$controls$hierarchy = TRUE</code>, <code>state_order</code> must
be a matrix of dimension <code>x$data$controls$states[1]</code> x
<code>x$data$controls$states[2] + 1</code>. 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
<code>state_order = matrix(c(2,1,2,1,1,2),2,3)</code> swaps the
coarse-scale states and the fine-scale states of coarse-scale state 2.</li>
</ul></dd></dl>

Arguments

Reorder estimated states — reorder_states

<dl>

<dt>x</dt>
<dd>An object of class <code>fHMM_model</code>.</dd>


<dt>state_order</dt>
<dd>A vector or a matrix which determines the new ordering.<ul>
<li>If <code>x$data$controls$hierarchy = FALSE</code>, <code>state_order</code> must
be a vector of length <code>x$data$controls$states</code> with integer
values from <code>1</code> to <code>x$data$controls$states</code>. If the old
state number <code>x</code> should be the new state number <code>y</code>, put
the value <code>x</code> at the position <code>y</code> of <code>state_order</code>.
E.g. for a 2-state HMM, specifying <code>state_order = c(2,1)</code> swaps
the states.</li>
<li>If <code>x$data$controls$hierarchy = TRUE</code>, <code>state_order</code> must
be a matrix of dimension <code>x$data$controls$states[1]</code> x
<code>x$data$controls$states[2] + 1</code>. 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
<code>state_order = matrix(c(2,1,2,1,1,2),2,3)</code> swaps the
coarse-scale states and the fine-scale states of coarse-scale state 2.</li>
</ul></dd>

</dl>

reorder_states: Reorder estimated states

Description

Usage

Value

Arguments

Examples