expectreg-package {expectreg} | R Documentation |
Expectile and Quantile Regression
Description
Expectile and quantile regression of models with nonlinear effects e.g. spatial, random, ridge using least asymmetric weighed squares / absolutes as well as boosting; also supplies expectiles for common distributions.
Details
Author(s)
Fabian Otto-Sobotka
Carl von Ossietzky University Oldenburg
https://uol.de
Elmar Spiegel
Helmholtz Centre Munich
https://www.helmholtz-munich.de
Sabine Schnabel
Wageningen University and Research Centre
https://www.wur.nl
Linda Schulze Waltrup
Ludwig Maximilian University Munich
https://www.lmu.de
with contributions from
Paul Eilers
Erasmus Medical Center Rotterdam
https://www.erasmusmc.nl
Thomas Kneib
Georg August University Goettingen
https://www.uni-goettingen.de
Goeran Kauermann
Ludwig Maximilian University Munich
https://www.lmu.de
Maintainer: Fabian Otto-Sobotka <fabian.otto-sobotka@uni-oldenburg.de>
References
Fenske N and Kneib T and Hothorn T (2009) Identifying Risk Factors for Severe Childhood Malnutrition by Boosting Additive Quantile Regression Technical Report 052, University of Munich
He X (1997) Quantile Curves without Crossing The American Statistician, 51(2):186-192
Koenker R (2005) Quantile Regression Cambridge University Press, New York
Schnabel S and Eilers P (2009) Optimal expectile smoothing Computational Statistics and Data Analysis, 53:4168-4177
Schnabel S and Eilers P (2011) Expectile sheets for joint estimation of expectile curves (under review at Statistical Modelling)
Sobotka F and Kneib T (2010) Geoadditive Expectile Regression Computational Statistics and Data Analysis, doi: 10.1016/j.csda.2010.11.015.
See Also
Examples
data(dutchboys)
## Expectile Regression using the restricted approach
ex = expectreg.ls(dist ~ rb(speed),data=cars,smooth="f",lambda=5,estimate="restricted")
names(ex)
## The calculation of expectiles for given distributions
enorm(0.1)
enorm(0.5)
## Introducing the expectiles-meet-quantiles distribution
x = seq(-5,5,length=100)
plot(x,demq(x),type="l")
## giving an expectile analogon to the 'quantile' function
y = rnorm(1000)
expectile(y)
eenorm(y)