Unknown Variance under an Exponential Allocation Assumption
Abstract
An exponential reward setup can imply a particular relationship between location and dispersion. Unknown-variance ranking asks how dispersion is learned in finite samples. Evaluation should test output shape and pilot information separately. A distributional formula cannot substitute for empirical evidence that rare observations or dependent records satisfy the assumed measurement model. This focused synthesis develops an empirical comparison that preserves the terminal action, observation process, and total verification cost. Its proposed tests are prospective; no new simulation run, model-training result, or intervention effect is reported.
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