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: Studies show rAR achieves higher precision (approx. ) and recall (approx. ) compared to other techniques like ARIMA. 3. Response-Adaptive Randomization (RAR)

In engineering and healthcare, refers to a Recursive Autoregressive Model used for real-time forecasting.

: It assumes decision-makers have reference-dependent preferences where the "reference point" itself is a random variable. Special Cases : Models.rar

If all preferences are identical, it reduces to a standard .

If there is an extreme bias toward the reference point, it becomes the . : Studies show rAR achieves higher precision (approx

) that exponentially discounts older data, ensuring the most recent measurements have the highest impact on predictions.

: It favors the "best" treatment based on accumulated results, making the trial more ethical by potentially assigning more patients to effective treatments. 4. Machine Learning & Vision Models Other "RAR" models appearing in technical archives include: Special Cases : If all preferences are identical,

: This method uses sequential Bayesian prediction to allocate patients to treatment arms.