Estimates conditional distributions and conditional quantiles. The versions of the methods in this package are primarily for use in multiple step procedures where the first step is to estimate a conditional distribution. In particular, there are functions for implementing distribution regression, quantile regression, and versions of local linear distribution regression; all in a unified framework. Distribution regression provides a way to flexibly model the distribution of some outcome Y conditional on covariates X without imposing parametric assumptions on the conditional distribution but providing more structure than fully nonparametric estimation (See Foresi and Peracchi (1995) <doi:10.2307/2291056> and Chernozhukov, Fernandez-Val, and Melly (2013) <doi:10.3982/ECTA10582>).
|Author||Brantly Callaway [aut, cre], Weige Huang [aut]|
|Maintainer||Brantly Callaway <[email protected]>|
|Package repository||View on CRAN|
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