summarise_tvarstar_posthoc

Produces a small summary table for nonlinear time-series models
such as TVAR and LSTAR, focusing on model status and AIC.

Provides tools for fitting bivariate hurdle negative binomial
models with horseshoe priors, Bayesian Model Averaging (BMA) via stacking,
and comprehensive causal inference methods including G-computation,
transfer entropy, Threshold Vector Autoregressive (TVAR) and Smooth
Transition Autoregressive (STAR) models, Dynamic Bayesian Networks (DBN),
Hidden Markov Models (HMM), and sensitivity analysis.

José Mauricio Gómez Julián

bivarhr

Bivariate Hurdle Regression with Bayesian Model Averaging

summarise_tvarstar_posthoc function

<dl><dt>tsdyn_res</dt>
<dd>A list of model objects, typically with elements
<code>$TVAR</code>, <code>$LSTAR_I</code>, <code>$LSTAR_C</code>, as returned by
a fitting routine based on the tsDyn package.</dd></dl>

Arguments

Summarise nonlinear time-series models (TVAR and LSTAR) — summarise_tvarstar_posthoc

<dl>

<dt>tsdyn_res</dt>
<dd>A list of model objects, typically with elements
<code>$TVAR</code>, <code>$LSTAR_I</code>, <code>$LSTAR_C</code>, as returned by
a fitting routine based on the tsDyn package.</dd>

</dl>

summarise_tvarstar_posthoc: Summarise nonlinear time-series models (TVAR and LSTAR)

Description

Usage

Value

Arguments

Details