expectreg-package: Expectile and Quantile Regression

Description Details Author(s) References See Also Examples

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

Package: expectreg
Type: Package
Version: 0.50
Date: 2019-08-22
License: GPL-2
LazyLoad: yes
LazyData: yes

Author(s)

Fabian Otto-Sobotka
Carl von Ossietzky University Oldenburg
http://www.uni-Oldenburg.de

Elmar Spiegel
Helmholtz Centre Munich
http://www.helmholtz-muenchen.de

Sabine Schnabel
Wageningen University and Research Centre
http://www.wur.nl

Linda Schulze Waltrup
Ludwig Maximilian University Munich
http://www.lmu.de

with contributions from

Paul Eilers
Erasmus Medical Center Rotterdam
http://www.erasmusmc.nl

Thomas Kneib
Georg August University Goettingen
http://www.uni-goettingen.de

Goeran Kauermann
Ludwig Maximilian University Munich
http://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

mboost, BayesX

Examples

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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)

Example output

Loading required package: parallel
Loading required package: mboost
Loading required package: stabs
This is mboost 2.9-1. See 'package?mboost' and 'news(package  = "mboost")'
for a complete list of changes.

Loading required package: BayesX
Loading required package: shapefiles
Loading required package: foreign

Attaching package: 'shapefiles'

The following objects are masked from 'package:foreign':

    read.dbf, write.dbf

Note: Function plotsurf depends on akima which has
 a restricted licence that explicitly forbids commercial use.
 akima is therefore disabled by default and may be enabled by
 akimaPermit(). Calling this function includes your agreement to
 akima`s licence restrictions.
 [1] "lambda"         "intercepts"     "coefficients"   "values"        
 [5] "response"       "covariates"     "formula"        "asymmetries"   
 [9] "effects"        "helper"         "design"         "bases"         
[13] "fitted"         "covmat"         "trend.coef"     "residual.coef" 
[17] "asymmetry.coef" "predict"       
[1] -0.8615921
[1] 0
      0    0.25     0.5    0.75       1 
-3.0899 -0.4030  0.0401  0.4762  3.4076 
$x
 [1] -1.692499727 -1.451129848 -1.303704826 -1.195870923 -1.110128291
 [6] -1.038541520 -0.976819654 -0.922372890 -0.873515032 -0.829085319
[11] -0.788249769 -0.750388508 -0.715027899 -0.681797644 -0.650402572
[16] -0.620603457 -0.592203596 -0.565039192 -0.538972312 -0.513885633
[21] -0.489678455 -0.466263639 -0.443565205 -0.421516451 -0.400058438
[26] -0.379138778 -0.358710639 -0.338731937 -0.319164659 -0.299974306
[31] -0.281129419 -0.262601182 -0.244363085 -0.226390632 -0.208661092
[36] -0.191153283 -0.173847385 -0.156724773 -0.139767871 -0.122960025
[41] -0.106285388 -0.089728811 -0.073275757 -0.056912210 -0.040624597
[46] -0.024399716 -0.008224667  0.007913211  0.024026406  0.040127288
[51]  0.056228170  0.072341365  0.088479243  0.104654292  0.120879173
[56]  0.137166786  0.153530334  0.169983387  0.186539964  0.203214601
[61]  0.220022447  0.236979349  0.254101961  0.271407859  0.288915668
[66]  0.306645208  0.324617661  0.342855758  0.361383995  0.380228882
[71]  0.399419235  0.418986513  0.438965215  0.459393354  0.480313015
[76]  0.501771027  0.523819781  0.546518215  0.569933032  0.594140209
[81]  0.619226888  0.645293768  0.672458172  0.700858033  0.730657148
[86]  0.762052220  0.795282475  0.830643085  0.868504345  0.909339895
[91]  0.953769608  1.002627466  1.057074230  1.118796096  1.190382867
[96]  1.276125499  1.383959402  1.531384424  1.772754303

$y
 [1] -1.6869 -1.4436 -1.2949 -1.1899 -1.1084 -1.0418 -0.9837 -0.9318 -0.8842
[10] -0.8405 -0.8000 -0.7622 -0.7267 -0.6932 -0.6612 -0.6307 -0.6014 -0.5733
[19] -0.5462 -0.5201 -0.4949 -0.4708 -0.4476 -0.4250 -0.4030 -0.3817 -0.3611
[28] -0.3409 -0.3211 -0.3017 -0.2827 -0.2640 -0.2456 -0.2275 -0.2096 -0.1920
[37] -0.1745 -0.1572 -0.1401 -0.1232 -0.1064 -0.0897 -0.0732 -0.0568 -0.0405
[46] -0.0243 -0.0081  0.0080  0.0241  0.0401  0.0562  0.0722  0.0882  0.1043
[55]  0.1204  0.1366  0.1528  0.1691  0.1855  0.2020  0.2186  0.2354  0.2523
[64]  0.2694  0.2868  0.3043  0.3221  0.3402  0.3586  0.3773  0.3963  0.4156
[73]  0.4353  0.4555  0.4762  0.4973  0.5190  0.5416  0.5649  0.5892  0.6143
[82]  0.6402  0.6671  0.6951  0.7244  0.7553  0.7879  0.8224  0.8594  0.8993
[91]  0.9430  0.9910  1.0445  1.1073  1.1807  1.2691  1.3807  1.5341  1.8004

expectreg documentation built on Aug. 24, 2019, 1:05 a.m.