对预指定校正的协变量平衡进行随时有效的确认
Anytime-Valid Confirmation of Covariate Balance for Prespecified Corrections
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中文总结 AI 辅助
研究对协变量转移适应中预指定校正的随时有效确认，提出确认协变量平衡程序，给出时间均匀置信序列等方法及相关检验，用于控制错误确认、监测可接受区域等，展示了有限源效应及下游共形覆盖等实验结果。
中文摘要 AI 辅助
许多协变量转移适应方法构建校正 \(w(x)\)，但用户仍需确定校正后的分布对于目标流是否足够平衡。我们研究从顺序未标记目标输入对预指定校正进行随时有效的确认。主要贡献是一种确认协变量平衡的程序。对于预指定的平衡函数类和容差，时间均匀置信序列允许持续监测和数据依赖停止。停止时，该程序会产生针对所选函数和容差的局部证书，并提供普通转移诊断通常不具备的绝对下游充分性声明。有有限源数据时，收缩带在考虑加权源矩不确定性的同时保留此保证，而扩展带仅支持兼容性诊断。作为补充信息，我们研究了源校准似然比电子过程，其 KL 漂移恒等式表征相对于源的校正方向。在源参考分布下，控制越过其证据阈值的概率，但越过并不确认平衡。我们还给出了超出可接受校正区域的偏离的指数倾斜检验，并在加权共形预测中部署平衡确认的校正。实验说明了错误确认控制、对平衡函数类的局部性、KL 漂移诊断、可接受区域监测、有限源效应以及协变量转移下的下游共形覆盖。
英文摘要
Many covariate-shift adaptation methods construct a correction $w(x)$, but users must still determine whether the corrected distribution is sufficiently balanced for the target stream. We study anytime-valid confirmation of prespecified corrections from sequential unlabeled target inputs. Our primary contribution is a procedure for confirming covariate balance. For a prespecified class of balancing functions and tolerances, time-uniform confidence sequences permit continuous monitoring and data-dependent stopping once all plausible target moments lie within their tolerance bands. If the correction is out of tolerance for at least one function, the probability of ever incorrectly confirming balance is at most the prescribed level. Upon stopping, the procedure yields a certificate local to the chosen functions and tolerances, yet providing an absolute downstream-adequacy statement that ordinary shift diagnostics generally do not. With finite source data, contracted bands preserve this guarantee while accounting for uncertainty in weighted source moments, whereas expanded bands support only compatibility diagnostics. As complementary information, we study a source-calibrated likelihood-ratio e-process whose KL-drift identity characterizes correction directions relative to the source. Under the source-reference distribution, the probability of ever crossing its evidence threshold is controlled, but crossing does not confirm balance. We also give an exponential-tilt test for departures beyond an acceptable correction region and deploy balance-confirmed corrections in weighted conformal prediction. Experiments illustrate false-confirmation control, locality to the balancing-function class, KL-drift diagnostics, acceptable-region monitoring, finite-source effects, and downstream conformal coverage under covariate shift.
