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  "Title": "Augmented Balancing Weights as Linear Regression",
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  "Description": "Implements augmented balancing weights for causal\ninference and linear functional estimation based on David\nBruns-Smith, Oliver Dukes, Avi Feller, and Elizabeth L. Ogburn\n(2026) <doi:10.1093/jrsssb/qkaf019>. Establishes numerical\nequivalence between augmented balancing weight estimators and\nsingle linear models with weighted regression coefficients.\nProvides flexible routines for double ridge (l2 balancing),\ndouble lasso (l-infinity balancing), and generalized augmented\nlinear outcome models. Features cross-validation procedures for\ntuning outcome penalty parameters, covariate balance, and Riesz\nloss. Supports robust influence-function-based standard errors,\nbootstrap confidence intervals, balance diagnostic tools, and\ncounterfactual prediction for treatment effects such as average\ntreatment effect (ATE) and average treatment effect on the\ntreated (ATT), expanding upon the doubly robust estimation\nframework established by Robins, Rotnitzky, and Zhao (1994)\n<doi:10.1080/01621459.1994.10476818> and Chernozhukov,\nChetverikov, Demirer, Duflo, Hansen, Newey, and Robins (2018)\n<doi:10.1111/ectj.12097>.",
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