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Simulation-based estimators ensure accurate predictions in complex models.
The article shows that using simulation-based methods with nonparametric maximum likelihood estimators can give accurate results in statistical modeling. When the model is correct, the estimated uncertainty matches the theoretical predictions. This is based on how well the estimators converge and a specific mathematical theorem.