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On Classical Measurement Error within a Bayesian Nonparametric Framework
DOI:10.1007/978-3-031-12766-3_24.png)
摘要
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This paper studies the impact of classical measurement error on a Dependent Dirichlet Process (DDP). Specifically, we study a Simulation-Extrapolation (SIMEX) algorithm, adapted to a nonparametric Bayesian framework, that assesses the impact of measurement error by inducing even further error in the covariate. We illustrate the algorithm via a battery of numerical experiments.
Keyword:
Classical measurement error
Dependent Dirichlet process
Nonparametric Bayes
Simulation-extrapolation
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