lldr.inner.y

a particular value of y to compute local linear distribution
regression for

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

calls lldr.inner.xvals for a particular value of y. This is a
 dummy function that just reverses the arguments of lldr.inner.xvals in
 order to be able to call it for a vector of y values

internal

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>).

lldr.inner.y: lldr.inner.y

Description

Usage

Arguments

Value