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@article{barber1996quickhull,
	Author = {Barber, C Bradford and Dobkin, David P and Huhdanpaa, Hannu},
	Date-Added = {2020-07-20 15:09:39 -0700},
	Date-Modified = {2020-07-20 15:09:51 -0700},
	Journal = {{ACM Transactions on Mathematical Software (TOMS)}},
	Number = {4},
	Pages = {469-483},
	Publisher = {Acm New York, NY, USA},
	Title = {The quickhull algorithm for convex hulls},
	Volume = {22},
	Year = {1996}}

@article{eddy1977new,
	Author = {Eddy, William F},
	Date-Added = {2020-07-20 15:05:14 -0700},
	Date-Modified = {2020-07-20 15:05:29 -0700},
	Journal = {{ACM Transactions on Mathematical Software (TOMS)}},
	Number = {4},
	Pages = {398-403},
	Publisher = {ACM New York, NY, USA},
	Title = {A new convex hull algorithm for planar sets},
	Volume = {3},
	Year = {1977}}

@book{kish_ess,
	Address = {New York},
	Author = {Leslie Kish},
	Date-Added = {2020-07-20 14:04:14 -0700},
	Date-Modified = {2020-07-20 14:04:14 -0700},
	Publisher = {John Wiley \& Sons},
	Title = {Survey Sampling},
	Year = {1965}}

@article{robins2000,
	Author = {Robins, James M and Hernan, Miguel Angel and Brumback, Babette},
	Date-Added = {2020-07-16 15:00:06 -0700},
	Date-Modified = {2020-07-16 15:00:06 -0700},
	Journal = {Epidemiology},
	Number = {5},
	Pages = {550-560},
	Publisher = {LWW},
	Title = {Marginal structural models and causal inference in epidemiology},
	Volume = {11},
	Year = {2000}}

@article{lee2011weight,
	Author = {Lee, Brian K and Lessler, Justin and Stuart, Elizabeth A},
	Date-Added = {2020-07-16 14:46:25 -0700},
	Date-Modified = {2020-07-16 14:46:25 -0700},
	Journal = {{PloS One}},
	Number = {3},
	Title = {Weight trimming and propensity score weighting},
	Volume = {6},
	Year = {2011}}

@article{crump2009dealing,
	Author = {Crump, Richard K and Hotz, V Joseph and Imbens, Guido W and Mitnik, Oscar A},
	Date-Added = {2020-07-16 14:46:11 -0700},
	Date-Modified = {2020-07-16 14:46:11 -0700},
	Journal = {Biometrika},
	Number = {1},
	Pages = {187-199},
	Publisher = {Oxford University Press},
	Title = {Dealing with limited overlap in estimation of average treatment effects},
	Volume = {96},
	Year = {2009}}

@article{tbbicke2020entropy,
	Archiveprefix = {{arXiv}},
	Author = {Stefan T{\"u}bbicke},
	Date-Added = {2020-07-16 13:59:43 -0700},
	Date-Modified = {2020-07-16 13:59:43 -0700},
	Eprint = {{2001.06281}},
	Journal = {{arXiv e-prints}},
	Primaryclass = {econ.EM},
	Title = {Entropy Balancing for Continuous Treatments},
	Year = {2020}}

@article{fong2018,
	Author = {Fong, Christian and Hazlett, Chad and Imai, Kosuke},
	Date-Added = {2020-07-16 13:59:37 -0700},
	Date-Modified = {2020-07-16 13:59:37 -0700},
	Journal = {Annals of Applied Statistics},
	Title = {Covariate balancing propensity score for a continuous treatment: application to the efficacy of political advertisements},
	Volume = {In-Press},
	Year = {2018}}

@article{zhu_boosting,
	Author = {Zhu, Yeying and Coffman, Donna L and Ghosh, Debashis},
	Date-Added = {2020-07-16 13:59:32 -0700},
	Date-Modified = {2020-07-16 13:59:32 -0700},
	Journal = {Journal of Causal Inference},
	Number = {1},
	Pages = {25-40},
	Title = {A boosting algorithm for estimating generalized propensity scores with continuous treatments},
	Volume = {3},
	Year = {2015}}

@article{kennedy2017,
	Abstract = {Summary Continuous treatments (e.g. doses) arise often in practice, but many available causal effect estimators are limited by either requiring parametric models for the effect curve, or by not allowing doubly robust covariate adjustment. We develop a novel kernel smoothing approach that requires only mild smoothness assumptions on the effect curve and still allows for misspecification of either the treatment density or outcome regression. We derive asymptotic properties and give a procedure for data-driven bandwidth selection. The methods are illustrated via simulation and in a study of the effect of nurse staffing on hospital readmissions penalties.},
	Author = {Kennedy, Edward H. and Ma, Zongming and McHugh, Matthew D. and Small, Dylan S.},
	Date-Added = {2020-07-16 13:59:28 -0700},
	Date-Modified = {2020-07-16 13:59:28 -0700},
	Journal = {{Journal of the Royal Statistical Society: Series B}},
	Number = {4},
	Pages = {1229-1245},
	Title = {Non-parametric methods for doubly robust estimation of continuous treatment effects},
	Volume = {79},
	Year = {2017},
	Bdsk-Url-1 = {https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/rssb.12212},
	Bdsk-Url-2 = {https://doi.org/10.1111/rssb.12212}}

@article{imai_causalGPS,
	Author = {Imai, Kosuke and Van Dyk, David A},
	Date-Added = {2020-07-16 13:32:33 -0700},
	Date-Modified = {2020-07-16 13:32:33 -0700},
	Journal = {Journal of the American Statistical Association},
	Number = {467},
	Pages = {854-866},
	Publisher = {Taylor \& Francis},
	Title = {Causal inference with general treatment regimes: generalizing the propensity score},
	Volume = {99},
	Year = {2004}}

@inproceedings{hirano_continuous,
	Address = {New York},
	Author = {Hirano, Keisuke and Imbens, Guido W},
	Booktitle = {Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives},
	Date-Added = {2020-07-16 13:32:29 -0700},
	Date-Modified = {2020-07-16 13:32:29 -0700},
	Editor = {Andrew Gelman and Xiao-Li Meng},
	Pages = {73-84},
	Publisher = {John Wiley \& Sons},
	Title = {The propensity score with continuous treatments},
	Year = {2004}}

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