On Asymptotic Analysis of the Two-Stage Approach: Towards Data-Driven Parameter Estimation

Fuente: arXiv
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Main Authors: Lakshminarayanan, Braghadeesh, Rojas, Cristian R.
Format: Preprint
Published: 2025
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author Lakshminarayanan, Braghadeesh
Rojas, Cristian R.
author_facet Lakshminarayanan, Braghadeesh
Rojas, Cristian R.
contents In this paper, we analyze the asymptotic properties of the Two-Stage (TS) estimator -- a simulation-based parameter estimation method that constructs estimators offline from synthetic data. While TS offers significant computational advantages compared to standard approaches to estimation, its statistical properties have not been previously analyzed in the literature. Under simple assumptions, we establish that the TS estimator is strongly consistent and asymptotically normal, providing the first theoretical guarantees for this class of estimators.
format Preprint
id arxiv_https___arxiv_org_abs_2508_18201
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On Asymptotic Analysis of the Two-Stage Approach: Towards Data-Driven Parameter Estimation
Lakshminarayanan, Braghadeesh
Rojas, Cristian R.
Systems and Control
Statistics Theory
In this paper, we analyze the asymptotic properties of the Two-Stage (TS) estimator -- a simulation-based parameter estimation method that constructs estimators offline from synthetic data. While TS offers significant computational advantages compared to standard approaches to estimation, its statistical properties have not been previously analyzed in the literature. Under simple assumptions, we establish that the TS estimator is strongly consistent and asymptotically normal, providing the first theoretical guarantees for this class of estimators.
title On Asymptotic Analysis of the Two-Stage Approach: Towards Data-Driven Parameter Estimation
topic Systems and Control
Statistics Theory
url https://arxiv.org/abs/2508.18201