tag:joss.theoj.org,2005:/papers/reviewed_by/@adibenderJournal of Open Source Software2022-09-23T14:45:34ZJournal of Open Source Softwarehttps://joss.theoj.orgtag:joss.theoj.org,2005:Paper/36132022-09-23T14:45:34Z2022-09-25T16:58:01Zhaldensify: Highly adaptive lasso conditional density estimation in Racceptedv0.2.52022-05-18 15:31:04 UTC772022-09-23 14:45:34 UTC720224522NimaS.HejaziDepartment of Biostatistics, T.H. Chan School of Public Health, Harvard University0000-0002-7127-2789MarkJ.van der LaanDivision of Biostatistics, School of Public Health, University of California, Berkeley, Department of Statistics, University of California, Berkeley0000-0002-1019-8343DavidBenkeserDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University0000-0002-1019-834310.21105/joss.04522https://doi.org/10.5281/zenodo.7089147Rhttps://joss.theoj.org/papers/10.21105/joss.04522.pdfmachine learning, causal inference, conditional density estimation, generalized propensity score, inverse probability weighting, semiparametric inference