fun.plot.q {GLDreg} | R Documentation |
2-D Plot for Quantile Regression lines
Description
This function plots quantile regression lines from GLD.lm
and
one of fun.gld.slope.vary.int.fixed
,
fun.gld.slope.fixed.int.vary
,
fun.gld.slope.fixed.int.vary.emp
,
fun.gld.all.vary.emp
, fun.gld.all.vary
,
fun.gld.slope.vary.int.fixed.emp
, GLD.quantreg
.
Usage
fun.plot.q(x, y, fit, quant.info, ...)
Arguments
x |
A numerical vector of explanatory variable |
y |
A numerical vector of response variable |
fit |
An object from |
quant.info |
An object from one of |
... |
Additional arguments to be passed to plot function, such as axis labels and title of the graph |
Details
This is intended to plot only two variables, for quantile regression involving more than one explanatory variable, consider plotting the actual values versus fitted values by fitting a secondary GLD quantile model between actual and fitted values.
Value
A graph showing quantile regression lines
Author(s)
Steve Su
References
Su (2015) "Flexible Parametric Quantile Regression Model" Statistics & Computing May 2015, Volume 25, Issue 3, pp 635-650
Examples
## Dummy example
## Create dataset
set.seed(10)
x<-rnorm(200,3,2)
y<-3*x+rnorm(200)
dat<-data.frame(y,x)
## Fit FKML GLD regression with 3 simulations
fit<-GLD.lm.full(y~x,data=dat,fun=fun.RMFMKL.ml.m,param="fkml",n.simu=3)
## Find median regression, use empirical method
med.fit<-GLD.quantreg(0.5,fit,slope="fixed",emp=TRUE)
fun.plot.q(x=x,y=y,fit=fit[[1]],med.fit, xlab="x",ylab="y")
## Not run:
## Plot result of quantile regression
## Extract the Engel dataset
library(quantreg)
data(engel)
## Fit GLD Regression along with simulations
engel.fit.all<-GLD.lm.full(foodexp~income,data=engel,
param="fmkl",fun=fun.RMFMKL.ml.m)
## Fit quantile regression from 0.1 to 0.9, with equal spacings between
## quantiles
result<-GLD.quantreg(seq(0.1,.9,length=9),engel.fit.all,intercept="fixed")
## Plot the quantile regression lines
fun.plot.q(x=engel$income,y=engel$foodexp,fit=engel.fit.all[[1]],result,
xlab="income",ylab="Food Expense")
## End(Not run)