A Bit of Information Theory, and the Data Augmentation Algorithm Converges
Yaming Yu

TL;DR
This paper uses information theory to prove a convergence theorem for the data augmentation algorithm, enhancing understanding of its theoretical foundations.
Contribution
It introduces a novel information-theoretic approach to establish convergence of the data augmentation algorithm.
Findings
Proves convergence of the DA algorithm using information theory
Provides a new theoretical framework for analyzing DA algorithms
Enhances understanding of DA algorithm stability
Abstract
The data augmentation (DA) algorithm is a simple and powerful tool in statistical computing. In this note basic information theory is used to prove a nontrivial convergence theorem for the DA algorithm.
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