.read_te_all

Helper to load transfer entropy results from a combined CSV file or
from separate per-type files (counts, rates, binary) if the combined
file is not available.

internal

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

.read_te_all function

<dl><dt>dir_csv</dt>
<dd>Character scalar; directory where the transfer entropy
CSV files are stored.
The function first looks for <code>"transfer_entropy.csv"</code>. If present,
it is read and returned. Otherwise it attempts to read:<ul>
<li><code>"transfer_entropy_counts.csv"</code></li>
<li><code>"transfer_entropy_rates.csv"</code></li>
<li><code>"transfer_entropy_binary.csv"</code></li>
</ul>and combines them into a single data frame with a <code>type</code> column.</dd></dl>

Arguments

Read transfer entropy results from CSV files — .read_te_all

<dl>

<dt>dir_csv</dt>
<dd>Character scalar; directory where the transfer entropy
CSV files are stored.
The function first looks for <code>"transfer_entropy.csv"</code>. If present,
it is read and returned. Otherwise it attempts to read:<ul>
<li><code>"transfer_entropy_counts.csv"</code></li>
<li><code>"transfer_entropy_rates.csv"</code></li>
<li><code>"transfer_entropy_binary.csv"</code></li>
</ul>and combines them into a single data frame with a <code>type</code> column.</dd>

</dl>

.read_te_all: Read transfer entropy results from CSV files

Description

Usage

Value

Arguments