lldrs.inner

a vector of y values to compute F(y|x) for using local linear
distribution regression

y.seq

a vector of x values to compute F(y|x) using local
linear distribution regression

xmain.seq

a vector containing the data for the outcome

a vector containing the data for the "main" x variable

XMain

a matrix or data.frame containing the data for the "other"
x variables

XOther

"level" or "rank" determining whether method should
be used conditional on ytmin1 or the rank of ytmin1

method

The number of clusters to use, default is 1

internal function for running local linear distribution
 regression for a vector of y and x

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>).

lldrs.inner: lldrs.inner

Description

Usage

Arguments

Value