methods {expectreg} | R Documentation |
Methods for expectile regression objects
Description
Methods for objects returned by expectile regression functions.
Usage
## S3 method for class 'expectreg'
print(x, ...)
## S3 method for class 'expectreg'
summary(object,...)
## S3 method for class 'expectreg'
predict(object, newdata = NULL, with_intercept = T, ...)
## S3 method for class 'expectreg'
x[i]
## S3 method for class 'expectreg'
residuals(object, ...)
## S3 method for class 'expectreg'
resid(object, ...)
## S3 method for class 'expectreg'
fitted(object, ...)
## S3 method for class 'expectreg'
fitted.values(object, ...)
## S3 method for class 'expectreg'
effects(object, ...)
## S3 method for class 'expectreg'
coef(object, ...)
## S3 method for class 'expectreg'
coefficients(object, ...)
## S3 method for class 'expectreg'
confint(object, parm = NULL, level = 0.95, ...)
Arguments
x , object |
An object of class |
newdata |
Optionally, a data frame in which to look for variables with which to predict. |
with_intercept |
Should the intercept be added to the prediction of splines? |
i |
Covariate numbers to be kept in subset. |
level |
Coverage probability of the generated confidence intervals. |
parm |
Optionally the confidence intervals may be restricted to certain covariates, to be named in a vector. Otherwise the confidence intervals for the fit are returned. |
... |
additional arguments passed over. |
Details
These functions can be used to extract details from fitted models.
print
shows a dense representation of the model fit.
[
can be used to define a new object with a subset of covariates from the original fit.
The function coef
extracts the regression coefficients for each covariate listed separately.
For the function expectreg.boost
this is not possible.
Value
[
returns a new object of class expectreg with a subset of covariates from the original fit.
resid
returns the residuals in order of the response.
fitted
returns the overall fitted values while
effects
returns the values
for each covariate in a list.
coef
returns a list of all regression coefficients separately for each covariate.
Author(s)
Fabian Otto- Sobotka
Carl von Ossietzky University Oldenburg
https://uol.de
Elmar Spiegel
Georg August University Goettingen
https://www.uni-goettingen.de
References
Schnabel S and Eilers P (2009) Optimal expectile smoothing Computational Statistics and Data Analysis, 53:4168-4177
Sobotka F and Kneib T (2010) Geoadditive Expectile Regression Computational Statistics and Data Analysis, doi: 10.1016/j.csda.2010.11.015.
See Also
expectreg.ls
, expectreg.boost
, expectreg.qp
Examples
data(dutchboys)
expreg <- expectreg.ls(hgt ~ rb(age,"pspline"),data=dutchboys,smooth="f",
expectiles=c(0.05,0.2,0.8,0.95))
print(expreg)
coef(expreg)
new.d = dutchboys[1:10,]
new.d[,2] = 1:10
predict(expreg,newdata=new.d)