summary.tsissm.estimate

summary

Summary method for class &#8220;tsissm.estimate&#8221;

Unobserved components time series model using the linear innovations state space representation (single source of error) with choice of error distributions and option for dynamic variance. Methods for estimation using automatic differentiation, automatic model selection and ensembling, prediction, filtering, simulation and backtesting. Based on the model described in Hyndman et al (2012) <doi:10.1198/jasa.2011.tm09771>.

Alexios Ghalanos

tsissm

Linear Innovations State Space Unobserved Components Model

Alexios Galanos

summary.tsissm.estimate function

<dl><dt>object</dt>
<dd>an object of class &#8220;tsissm.estimate&#8221;.</dd>
<dt>vcov_type</dt>
<dd>the type of standard errors based on the vcov estimate (see <code><a href="/link/vcov?package=tsissm&version=1.0.1" data-mini-rdoc="tsissm::vcov">vcov</a></code>).</dd>
<dt>digits</dt>
<dd>integer, used for number formatting. Optionally, to avoid
scientific notation, set &#8216;options(scipen=999)&#8217;.</dd>
<dt>...</dt>
<dd>not currently used.</dd></dl>

Arguments

Model Estimation Summary — summary.tsissm.estimate

<dl>

<dt>object</dt>
<dd>an object of class &#8220;tsissm.estimate&#8221;.</dd>


<dt>vcov_type</dt>
<dd>the type of standard errors based on the vcov estimate (see <code><a href='https://rdrr.io/r/stats/vcov.html'>vcov</a></code>).</dd>


<dt>digits</dt>
<dd>integer, used for number formatting. Optionally, to avoid
scientific notation, set &#8216;options(scipen=999)&#8217;.</dd>


<dt>...</dt>
<dd>not currently used.</dd>

</dl>

summary.tsissm.estimate: Model Estimation Summary

Description

Usage

Value

Arguments