compute_ci

This helper function computes confidence intervals for the estimates of an
<code>fHMM_model</code> object using the inverse Fisher information.

internal

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 on the method. A user guide
is provided by the accompanying software paper "fHMM: Hidden Markov Models
for Financial Time Series in R", Oelschläger, L., Adam, T., and Michels, R.
(2024, Journal of Statistical Software) <doi:10.18637/jss.v109.i09>.

Lennart Oelschläger

fHMM

Fitting Hidden Markov Models to Financial Data

Timo Adam

Rouven Michels

compute_ci function

<dl><dt>x</dt>
<dd>[<code>fHMM_model</code>] 
An object of class <code>fHMM_model</code>.</dd>
<dt>alpha</dt>
<dd>[<code>numeric(1)</code>] 
The alpha level for the confidence interval. Must be between 0 and 1.
By default, <code>alpha = 0.05</code>, which computes a 95 percent confidence
interval.</dd></dl>

Arguments

Compute confidence intervals — compute_ci

<dl>

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


<dt>alpha</dt>
<dd>[<code>numeric(1)</code>] 
The alpha level for the confidence interval. Must be between 0 and 1.
By default, <code>alpha = 0.05</code>, which computes a 95 percent confidence
interval.</dd>

</dl>

compute_ci: Compute confidence intervals

Description

Usage

Value

Arguments