Package: TempleMetrics
Title: Estimating Conditional Distributions
Version: 1.2.0
Authors@R: c(
  person("Brantly", "Callaway", email = "brantly.callaway@temple.edu", role = c("aut","cre")), person("Weige", "Huang", email = "weige.huang@temple.edu", role=c("aut")))
Description: 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>).
Depends: R (>= 2.1.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: stats, BMisc, pbapply
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-12 17:29:10 UTC; tug82594
Author: Brantly Callaway [aut, cre],
  Weige Huang [aut]
Maintainer: Brantly Callaway <brantly.callaway@temple.edu>
Repository: CRAN
Date/Publication: 2018-09-12 17:40:03 UTC
