init_bilstm_model

Loads the trained BiLSTM model and associated scaler objects into memory.
Requires that Python dependencies have been set up via
<code>setup_python_deps</code>.

Provides tools and pre-trained Machine Learning [ML] models for
calibration of Agent-Based Models [ABMs] built with the R package
'epiworldR'. Implements methods described in Najafzadehkhoei, Vega Yon,
Modenesi, and Meyer (2025) <doi:10.48550/arXiv.2509.07013>. Users can
automatically calibrate ABMs in seconds with pre-trained ML models,
effectively focusing on simulation rather than calibration. Bridges a gap
by allowing public health practitioners to run their own ABMs without the
advanced technical expertise often required by calibration.

Sima Najafzadehkhoei

epiworldRcalibrate

Fast and Effortless Calibration of Agent-Based Models using
Machine Learning

init_bilstm_model function

<dl><dt>model_dir</dt>
<dd>Optional path to model directory. Defaults to the
package's bundled model files.</dd>
<dt>force_reload</dt>
<dd>Logical; reload even if already loaded.</dd></dl>

Arguments

Initialize BiLSTM Model for SIR Parameter Estimation — init_bilstm_model

<dl>

<dt>model_dir</dt>
<dd>Optional path to model directory. Defaults to the
package's bundled model files.</dd>


<dt>force_reload</dt>
<dd>Logical; reload even if already loaded.</dd>

</dl>

init_bilstm_model: Initialize BiLSTM Model for SIR Parameter Estimation

Description

Usage

Value

Arguments