draw_variance_scalar

Draws a variance from an inverse Wishart distribution.

internal

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

draw_variance_scalar function

<dl><dt>Y</dt>
<dd>dependent variable</dd>
<dt>nu</dt>
<dd>degrees of freedom, <code>nu&gt;p-1</code></dd>
<dt>s</dt>
<dd>scale matrix, <code>p x p</code></dd></dl>

Arguments

Draws a variance from an inverse Wishart distribution. — draw_variance_scalar

<dl>

<dt>Y</dt>
<dd>dependent variable</dd>


<dt>nu</dt>
<dd>degrees of freedom, <code>nu&gt;p-1</code></dd>


<dt>s</dt>
<dd>scale matrix, <code>p x p</code></dd>

</dl>

draw_variance_scalar: Draws a variance from an inverse Wishart distribution.

Description

Usage

Value

Arguments

Details