Nothing
###########################################################################
### Purpose: Compare predictions for quantile regression between rq() from
### the quantreg package and wrapper Rq() from the rms package
### Author: Ben Saville
### Date: 7/26/12
###########################################################################
library(quantreg)
library(rms)
### Simulate data
set.seed(1)
y = rnorm(1000,50,5)
age = sample(5:15,size=1000,replace=TRUE)
gender = as.factor(sample(c("male","female"),size=1000,replace=TRUE))
mydat = data.frame(y,age,gender)
#################### Using rq()
## Fit model with rq
k <- attr(rcs(age,4), 'parms')
rq.test = rq(y ~ rcs(age, k) + gender + rcs(age, k)*gender,
tau=0.50, data=mydat)
## Create dataset for predictions
p.age = rep(5:15,2)
p.gender = as.factor(rep(c("male","female"),each=11))
p.data = data.frame(p.age,p.gender)
names(p.data) = c("age","gender")
## Predictions using predict()
rq.preds = cbind(p.data, predict(rq.test, newdata=p.data))
## Predictions using X %*% Beta
p.gender.num = as.numeric(p.gender)-1
X.p = cbind(1, rcs(p.age, k), p.gender.num, rcs(p.age, k)*p.gender.num )
rq.preds.XB = X.p %*% rq.test$coefficients
## These match!
cbind(rq.preds,rq.preds.XB)
################## Using Rq()
## Fit model with Rq
Rq.test = Rq(y~ rcs(age, k) + gender + rcs(age, k)*gender,
tau=0.5, data=mydat)
## prediction using Predict()
Rq.preds = Predict(Rq.test, age=5:15, gender=c("male","female"),conf.int=FALSE)
## Note predict(Rq.test, newdata=p.data) gives the same values as Predict()
## Using X %*% Beta
Rq.preds.XB = X.p %*% Rq.test$coefficients
## These don't match!
cbind(Rq.preds, Rq.preds.XB)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.