: Unlike standard random utility models, RAR can account for context-specific behaviors like the attraction effect . 2. Recursive Autoregressive Model (rAR)

: It employs a "forgetting factor" (typically around 0.6750.675

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

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

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

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

If there is an extreme bias toward the reference point, it becomes the .