haldensify: Highly adaptive lasso conditional density estimation in R

The haldensify R package serves as a toolbox for nonparametric conditional density estimation based on the highly adaptive lasso, a flexible nonparametric algorithm for the estimation of functional statistical parameters (e.g., conditional mean, hazard, density). Building upon an earlier proposal (Dz van der While conditional density estimation is a fundamental problem in statistics, arising naturally in a variety of applications (including machine learning), it plays a critical role in estimating the causal effects of continuous-or ordinal-valued treatments. In such settings this covariate-conditional treatment density has been termed the generalized propensity score