disc_terciles

Converts a numeric vector into an ordered factor with three levels
(low, medium, high) using deterministic percent ranks to break ties.

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

disc_terciles function

<dl><dt>x</dt>
<dd>Numeric vector to discretize.</dd></dl>

Arguments

Discretize Numeric Vector into Terciles — disc_terciles

<dl>

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

</dl>

disc_terciles: Discretize Numeric Vector into Terciles

Description

Usage

Value

Arguments

Examples