lprq2: Local Linear Regression Methods for Conditional Quantile...

Description Usage Arguments Details Value Author(s) Examples

Description

Implements the local nonparametric method, local linear regression estimator with box kernel (default), for conditional quantile functions. This is a modification of Koenker's lprq ( from package quantreg).

Usage

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lprq2(x, y, h, xx, tau)

Arguments

x

The conditioning covariate

y

The response variable

h

The bandwidth parameter

xx

The points at which the function is to be estimated

tau

The quantile(s) to be estimated. This should be a list of quantiles if the function estimates the quantile process

Details

The function uses a box kernel.

Value

xx

The design points at which the evaluation occurs

fitted.values

The estimated function values at these design points

Author(s)

Wesley Graybill, Mingli Chen, Victor Chernozhukov, Ivan Fernandez-Val, Alfred Galichon

Examples

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require(quantreg)
data(GrowthChart)
attach(GrowthChart)

ages <- unique(sort(age))
llq.fit1 <- lprq2(age,height,h=1,xx=ages,tau=0.2)
detach(GrowthChart)

Rearrangement documentation built on May 1, 2019, 11:29 p.m.