compute_mcmc_results

Computes estimation results for the MCMC sampling output for a
specific HPDI and evaluation function (e.g. mean or median).

Determining potential output and the output gap - two inherently unobservable variables - is a major challenge for macroeconomists. 'sectorgap' features a flexible modeling and estimation framework for a multivariate Bayesian state space model identifying economic output fluctuations consistent with subsectors of the economy. The proposed model is able to capture various correlations between output and a set of aggregate as well as subsector indicators. Estimation of the latent states and parameters is achieved using a simple Gibbs sampling procedure and various plotting options facilitate the assessment of the results. For details on the methodology and an illustrative example, see Streicher (2024) <https://www.research-collection.ethz.ch/handle/20.500.11850/653682>.

Sina Streicher

sectorgap

Consistent Economic Trend Cycle Decomposition

compute_mcmc_results function

<dl><dt>model</dt>
<dd>state space model object, returned by the function
<code>define_ssmodel</code></dd>
<dt>settings</dt>
<dd>list with model setting, in the format returned by the
function <code>initialize_settings</code></dd>
<dt>mcmc</dt>
<dd>list with draws of parameters and states (including burnin phase)</dd>
<dt>data</dt>
<dd>list with at least two named components: <code>tsm</code> is a multiple
time series object that contains all observation series, <code>weights</code>
is a named list of time series with (nominal) weights, the list names
correspond to the different groups, i.e., <code>group1, group2, subgroup1</code>,
if present in the model</dd>
<dt>HPDIprob</dt>
<dd>probability of highest posterior density interval, optional
if <code>fit</code> is supplied</dd>
<dt>fit</dt>
<dd>(optional) an object of class <code>fit</code> (returned by the function
<code>estimate_ssmodel</code> and this function).</dd>
<dt>...</dt>
<dd>additional arguments (in case <code>fit</code> is supplied)</dd></dl>

Arguments

Results for sampled parameters and states — compute_mcmc_results

<dl>

<dt>model</dt>
<dd>state space model object, returned by the function
<code>define_ssmodel</code></dd>


<dt>settings</dt>
<dd>list with model setting, in the format returned by the
function <code>initialize_settings</code></dd>


<dt>mcmc</dt>
<dd>list with draws of parameters and states (including burnin phase)</dd>


<dt>data</dt>
<dd>list with at least two named components: <code>tsm</code> is a multiple
time series object that contains all observation series, <code>weights</code>
is a named list of time series with (nominal) weights, the list names
correspond to the different groups, i.e., <code>group1, group2, subgroup1</code>,
if present in the model</dd>


<dt>HPDIprob</dt>
<dd>probability of highest posterior density interval, optional
if <code>fit</code> is supplied</dd>


<dt>fit</dt>
<dd>(optional) an object of class <code>fit</code> (returned by the function
<code>estimate_ssmodel</code> and this function).</dd>


<dt>...</dt>
<dd>additional arguments (in case <code>fit</code> is supplied)</dd>

</dl>

compute_mcmc_results: Results for sampled parameters and states

Description

Usage

Value

Arguments

Details