kalman_filtering

Compute the filtered estimation of the parameters <code>theta</code> and <code>P</code>.

Inference methods for state-space models, relying on the Kalman Filter or on Viking (Variational Bayesian VarIance tracKING). See J. de Vilmarest (2022) <https://theses.hal.science/tel-03716104/>.

Joseph de Vilmarest

viking

State-Space Models Inference by Kalman or Viking

kalman_filtering function

<dl><dt>X</dt>
<dd>the explanatory variables</dd>
<dt>y</dt>
<dd>the time series</dd>
<dt>theta1</dt>
<dd>initial <code>theta</code></dd>
<dt>P1</dt>
<dd>initial <code>P</code></dd>
<dt>Q</dt>
<dd>(optional, default <code>0</code>) covariance matrix of the state noise</dd>
<dt>sig</dt>
<dd>(optional, default <code>1</code>) variance of the spate noise</dd></dl>

Arguments

Kalman Filtering — kalman_filtering

<dl>

<dt>X</dt>
<dd>the explanatory variables</dd>


<dt>y</dt>
<dd>the time series</dd>


<dt>theta1</dt>
<dd>initial <code>theta</code></dd>


<dt>P1</dt>
<dd>initial <code>P</code></dd>


<dt>Q</dt>
<dd>(optional, default <code>0</code>) covariance matrix of the state noise</dd>


<dt>sig</dt>
<dd>(optional, default <code>1</code>) variance of the spate noise</dd>

</dl>

kalman_filtering: Kalman Filtering

Description

Usage

Value

Arguments