Joint Constraints on a Locally Fitted Partition
Abstract
Partition regression can organize feasibility but may approximate a joint boundary poorly. Evaluation should retain common-run constraint outputs and directly measure favored candidates near limiting regions. Separate marginal intervals cannot establish a joint claim, and a finer partition has a cost. The selected action needs checking outside the observations that made it appear attractive. 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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