<ul><li>The study presents a model for estimating Ethereum transaction speeds, focusing on simplicity and transparency.</li><li>They evaluate the accuracy of prediction models provided by Etherscan and EthGasStation.</li><li>A post-hoc study aims to derive a simpler, more interpretable model compared to existing models.</li><li>Utilizing linear regression for prediction while engineering a historical feature for Ethereum transaction processing.</li><li>The study uses a sliding-time-window-based model validation approach for robustness.</li><li>Comparative analysis with state-of-the-practice model reveals similar accuracy at a global level.</li><li>The linear regression model outperforms for 'very cheap' and 'cheap' price categories.</li><li>Findings show potential cost-saving opportunities for users based on accurate predictions.</li><li>Authors include Michael Pacheco, Gustavo A. Oliva, Gopi Krishnan Rajbahadur, and Ahmed E. Hassan.</li><li>The paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.</li></ul>

A Simple, Transparent Model for Estimating Ethereum Transaction Speeds

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