Learn R Programming

quantreg.nonpar (version 1.0)

Nonparametric Series Quantile Regression

Description

Implements the nonparametric quantile regression method developed by Belloni, Chernozhukov, and Fernandez-Val (2011) to partially linear quantile models. Provides point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. Provides pointwise and uniform confidence intervals using analytic and resampling methods.

Copy Link

Version

Install

install.packages('quantreg.nonpar')

Monthly Downloads

111

Version

1.0

License

GPL (>= 2)

Last Published

April 1st, 2016

Functions in quantreg.nonpar (1.0)

npqr

Nonparametric Series Quantile Regression
load.sum

Appropriate Summary Statistics for Factors, Ordered Factors, and Numeric Variables
dpoly

Compute Derivative of Orthogonal Polynomials
removeI

Remove I() Tags From Formula
india

Childhood Malnutrition in India
wbootstrap

Weighted Bootstrap Inference for NPQR
no.process

Estimation for NPQR with No Inference
poly.wrap

Orthogonal Polynomial Wrapper
pivotal

Pivotal Process Inference for NPQR
ddpoly

Compute Second Derivative of Orthogonal Polynomials
quantreg.nonpar-package

Nonparametric Series Quantile Regression
msqrt

Square Root of Matrix by Spectral Decomposition
gaus

Gaussian Process Inference for NPQR
formulaDeriv

Derivative of Right Hand Side of Formula
gbootstrap

Gradient Bootstrap Inference for NPQR