summary.dfm

summary method for class <code>"dfm"</code>.

Assists in the set-up of algorithms for Bayesian inference of vector autoregressive (VAR) and error correction (VEC) models. Functions for posterior simulation, forecasting, impulse response analysis and forecast error variance decomposition are largely based on the introductory texts of Chan, Koop, Poirier and Tobias (2019, ISBN: 9781108437493), Koop and Korobilis (2010) <doi:10.1561/0800000013> and Luetkepohl (2006, ISBN: 9783540262398).

Franz X. Mohr

bvartools

Bayesian Inference of Vector Autoregressive and Error Correction
Models

summary.dfm function

<dl><dt>object</dt>
<dd>an object of class <code>"dfm"</code>, usually, a result of a call to
<code>dfm</code>.</dd>
<dt>ci</dt>
<dd>a numeric between 0 and 1 specifying the probability of the credible band.
Defaults to 0.95.</dd>
<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Summarising Bayesian Dynamic Factor Models — summary.dfm

<dl>

<dt>object</dt>
<dd>an object of class <code>"dfm"</code>, usually, a result of a call to
<code>dfm</code>.</dd>


<dt>ci</dt>
<dd>a numeric between 0 and 1 specifying the probability of the credible band.
Defaults to 0.95.</dd>


<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

summary.dfm: Summarising Bayesian Dynamic Factor Models

Description

Usage

Value

Arguments