{ "_id": "6a102e92acfb0bcc41c94575", "Package": "haldensify", "Title": "Highly Adaptive Lasso Conditional Density Estimation", "Version": "0.2.8", "Authors@R": "c(\nperson(\"Nima\", \"Hejazi\", email = \"nh@nimahejazi.org\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-7127-2789\")),\nperson(\"David\", \"Benkeser\", email = \"benkeser@emory.edu\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-1019-8343\")),\nperson(\"Mark\", \"van der Laan\", email = \"laan@berkeley.edu\",\nrole = c(\"aut\", \"ths\"),\ncomment = c(ORCID = \"0000-0003-1432-5511\")),\nperson(\"Rachael\", \"Phillips\", email = \"rachaelvphillips@berkeley.edu\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0002-8474-591X\"))\n)", "Maintainer": "Nima Hejazi ", "Description": "An algorithm for flexible conditional density estimation\nbased on application of pooled hazard regression to an\nartificial repeated measures dataset constructed by\ndiscretizing the support of the outcome variable. To facilitate\nflexible estimation of the conditional density, the highly\nadaptive lasso, a non-parametric regression function shown to\nestimate cadlag (RCLL) functions at a suitably fast convergence\nrate, is used. The use of pooled hazards regression for\nconditional density estimation as implemented here was first\ndescribed for by Díaz and van der Laan (2011)\n. Building on the conditional\ndensity estimation utilities, non-parametric inverse\nprobability weighted (IPW) estimators of the causal effects of\nadditive modified treatment policies are implemented, using\nconditional density estimation to estimate the generalized\npropensity score. Non-parametric IPW estimators based on this\ncan be coupled with undersmoothing of the generalized\npropensity score estimator to attain the semi-parametric\nefficiency bound (per Hejazi, Díaz, and van der Laan\n).", "License": "MIT + file LICENSE", "URL": "https://codex.nimahejazi.org/haldensify/", "BugReports": "https://github.com/nhejazi/haldensify/issues", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "RoxygenNote": "7.3.2", "RdMacros": "Rdpack", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://nhejazi.r-universe.dev", "Date/Publication": "2026-05-12 20:29:11 UTC", "RemoteUrl": "https://github.com/nhejazi/haldensify", "RemoteRef": "HEAD", "RemoteSha": "e4115e91322db1e71f6cc55717c6733ce58b260f", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-12 21:51:03 UTC", "User": "root" }, "Author": "Nima Hejazi [aut, cre, cph] (ORCID:\n),\nDavid Benkeser [aut] (ORCID: ),\nMark van der Laan [aut, ths] (ORCID:\n),\nRachael Phillips [ctb] (ORCID: )", "MD5sum": 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