make_lags

Creates a matrix of lagged values for a numeric vector.

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

make_lags function

<dl><dt>x</dt>
<dd>Numeric vector.</dd>
<dt>k</dt>
<dd>Integer; maximum lag order.</dd></dl>

Arguments

Create Lag Matrix — make_lags

<dl>

<dt>x</dt>
<dd>Numeric vector.</dd>


<dt>k</dt>
<dd>Integer; maximum lag order.</dd>

</dl>

make_lags: Create Lag Matrix

Description

Usage

Value

Arguments