replica

Create, enrich, validate and organise synthetic populations.

replica is an R library for generating synthetic populations of individual agents and households from aggregated demographic data.

The library provides tools for:

• creating synthetic agents from marginal distributions and contingency tables;

• assigning additional attributes using demographic reference data;

• generating synthetic households;

• validating synthetic population quality; and

• visualising goodness-of-fit.

The package implements and extends synthetic population generation methods described by de Mooij et al. (2024) and is designed to support health-economic microsimulation modelling and other simulation workflows.

Workflow

The workflow supported by replica can be summarised as:

Aggregate Counts
       ↓
make_agents()
       ↓
Synthetic Agents
       ↓
ReplicaAdder
       ↓
Enriched Population
       ↓
ReplicaStructure
       +
ReplicaGrouper
       ↓
Synthetic Households
       ↓
Validation

Getting Started

replica documentation is organised around the complete synthetic-population workflow.

To install a development version of replica, run the following commands in your R console:

utils::install.packages("devtools")

devtools::install_github("ready4-dev/replica")

1. Creating Synthetic Agents

Learn how to create individual synthetic agents from aggregate count data.

Key function:

make_agents()

2. Assigning Attributes Using Contingency Tables

Learn how to enrich synthetic agents using demographic contingency tables.

Key class:

ReplicaAdder

3. Generating Synthetic Households

Learn how to transform enriched agents into realistic household structures.

Key classes:

ReplicaStructure
ReplicaGrouper

4. Evaluating Synthetic Population Quality

Learn how to compare synthetic populations with reference data and assess population quality.

Key functions:

validate_synthetic_population_fit()

plot_validation_distributions()

plot_validation_differences()

plot_validation_heatmap()

Current Status

replica is under active development.

Library classes, syntax, documentation and workflows continue to evolve as additional functionality is implemented and tested.

This library should currently be used only for exploratory purposes.

Use of AI

replica code, tests and documentation (including vignettes) have all been authored by a human-machine partnership.

Microsoft Copilot has been used intensively in the development of this library.

References

de Mooij J, Sonnenschein T, Pellegrino M, Dastani M, Ettema D, Logan B and Verstegen JA (2024).

GenSynthPop: generating a spatially explicit synthetic population of individuals and households from aggregated data.

Autonomous Agents and Multi-Agent Systems.

https://link.springer.com/article/10.1007/s10458-024-09680-7