Package: kernR 0.8.2

kernR: Kernel-Based Causal Distributional Testing

Kernel-based hypothesis tests for causal inference and distributional treatment effects. Implements backdoor-adjusted HSIC (bd-HSIC) for testing causal association, and doubly robust kernel statistics (DR-DATE, DR-DETT) for testing distributional treatment effects beyond mean shifts. Supports binary, continuous, and mixed treatments, hierarchical/nested data structures, and scales to large datasets via Nystrom approximation and random Fourier features. This package depends on 'PESTO' (GPL (>= 3)); kernR's own sources are released under the MIT licence, but the installed combination with 'PESTO' is a combined work subject to the terms of the GPL (>= 3).

Authors:Max Moldovan [aut, cre, cph]