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因果函数的核方法：剂量、异质性与增量响应曲线AI 解读

Abstract We propose estimators based on kernel ridge regression for nonparametric causal functions such as dose, heterogeneous and incremental response curves. The treatment and covariates may be discrete or continuous in general spaces. Because of a decomposition property specific to the reproducing kernel Hilbert space, our estimators have simple closed-form solutions. We prove uniform consistency with finite sample rates via an original analysis of generalized kernel…

关于《多元依赖的多尺度 Fisher 独立性检验》的讨论AI 解读

We read with interest the work of Gorsky & Ma (2022) on statistical dependence testing using a multi-scale Fisher’s independence test, MultiFIT. The procedure consists of first transforming the data to map to the unit ball, then performing univariate Fisher’s exact tests of independence on a collection of |$2 \times 2$| contingency tables, and finally correcting for the use of multiple testing. The collection is obtained using a divide-and-conquer approach with a…