Dear all,
I am currently running an experiment using quantile regression. In order to get
more accurate results for a hypothesis test, I need to run a bootstrapping
version of quantile regression and I need to find the estimated covariance
matrix among all the coefficients for several quantiles
Dear all,
I would like to know how to print the variance-covariance matrix used in the
function anova.rq () when investigating whether the coefficients of a quantile
regression model is the same for a range of quantiles. To be more precise, when
I use the function summary.rq(, cov=TRUE) conside
Dear all,
I am doing a simulation for my model that works when I use only the rq()
command. However, since I need to use the varcov matrix for my Wald test, I
need to compute summary(rq(), cov=TRUE). But the simulation does not work
because of the error: tau + h > 1: error in summary.rq
I tr
Dear all,
I am trying to design a Wald test to verify whether some coefficients are
statistically equal.
I would like to test not only whether they are jointly equal for a given
quantile, but for a range of quantiles. Hence, I need to extract the
variance-covariance matrix among the coefficient
gt; To: julia.l...@hotmail.co.uk
>
> I'm not at my desk so this is untested, but I'm pretty sure double brackets
> will do the trick:
>
> qf2_1[[3]]
>
> M
>
> On Dec 5, 2011, at 7:14 AM, Julia Lira wrote:
>
> >
> > Dear all,
> >
> > I
Dear all,
I need to extract the covariance matrix of my quantile regression estimation to
use in a test. My regression is:
qf2_1 <- summary(rq(wb2 ~ apv2 + vol2, tau = phi2[1]), cov = TRUE)
I can extract the covaraince matrix by using: qf2_1 [3]. However, if I try to
use it in the test, it do
Dear all,
I need to run a simple linear regression such that:
y = b0 + b1*x1 + (1-b1)*x2 + e
which I know I can use:
lm(y ~ I(x1 - x2) + offset(x2)).
However, I also need to restrict the coefficient b1 to be between 0 and 1.
Is there any way to include such restriction in the linear regression
es
Dear all,
I am trying to compare the estimated coefficients of a quantile regression
model between two different samples. It is a Wald test, but I cannot find one
way to do that in R.The samples are collected conditional on a specific
characteristic and I would like to test whether such charact
y (sometimes a dubious practice because if you then remove
> > nonlinear terms you are mildly cheating).
> >
> > require(rms)
> > f <- Rq(y ~ x1 + rcs(x2,4), tau=.25)
> > anova(f) # tests associations and nonlinearity of x2
> >
> > Frank
> >
> >
Dear all,
I would like to know whether any specification test for linear against
nonlinear model hypothesis has been implemented in R using the quantreg
package.
I could read papers concerning this issue, but they haven't been implemented at
R. As far as I know, we only have two specificatio
Dear all,
I sent an email on Friday asking about nlrq {quantreg}, but I haven't received
any answer.
I need to estimate the quantile regression estimators of a model as: y =
exp(b0+x'b1+u). The model is nonlinear in parameters, although I can linearise
it by using log.When I write:
fitnl <- nlr
Dear all,
I need to run a quantile regression to estimate the coefficients of the
following model: Q_{Y}(Ï|X)=exp(βâ(Ï)+Xâ²Î²â(Ï)).
Since the model is nonlinear, I need to use nlrq(.). However, if I try
nlrq(Y~exp(X), tau=Ï), the software does not accept and also does not
unders
Dear all,
I need to do a loop as following:
#Consider a matrix:
M <- matrix(1, nrow=10, ncol=20)
#Matrices to store the looping results
M1 <- matrix(0, nrow=10, ncol=400)
h <- c(1:20/1000)
#loop
for (j in h){
M1 <- M/(2*j)
}
But this means that the first 20 columns of matrix M
roject.org
> Subject: Re: [R] loop
>
> Julia,
>
> Can you provide a reproducible example? Your code calls the
> 'rq' function which is not found on my system.
>
> Any paring down of the code to make it more readable would
> help us help yo
Dear all,
I have just sent an email with my problem, but I think no one can see the red
part, beacuse it is black. So, i am writing again the codes:
rm(list=ls()) #remove almost everything in the memory
set.seed(180185)
nsim <- 10
mresultx <- matrix(-99, nrow=1000, ncol=nsim)
mresultb <- ma
Dear all,
I have just sent an email with my problem, but I think no one can see the red
part, beacuse it is black. So, i am writing again the codes:
rm(list=ls()) #remove almost everything in the memory
set.seed(180185)
nsim <- 10
mresultx <- matrix(-99, nrow=1000, ncol=nsim)
mresultb <-
Dear all,
I am trying to run a loop in my codes, but the software returns an error:
"subscript out of bounds"
I dont understand exactly why this is happenning. My codes are the following:
rm(list=ls()) #remove almost everything in the memory
set.seed(180185)
nsim <- 10
mresultx <- ma
; > ## Do something that generates variable qf05
> >
> > M[i,] <- coeff(qf05)
> > }
> >
> > then M would be a nsim by 2 matrix, with each row holding the
> > coefficients from a different simulation. You could also look at
> > removing the loop by vectorisi
: [R] quantile regression
From: minhua...@gmail.com
To: julia.l...@hotmail.co.uk
You should define M as a vector or matrix depending on the length of coef(qf05)
and let M[i] or M[,i] be coef(qf05).
On Thu, Oct 7, 2010 at 6:40 PM, Julia Lira wrote:
Dear all,
I am a new user in r and
Dear all,
I am a new user in r and I am facing some problems with the quantile regression
specification. I have two matrix (mresultb and mresultx) with nrow=1000 and
ncol=nsim, where I specify (let's say) nsim=10. Hence, the columns in my matrix
represents each simulation of a determined va
Dear all,
I need to do a loop in R, but I am not sure the software is generating "n"
times the variables I request differently. When I ask to print the last matrix
created, I just can see the loop for n=1.
To be more precise, supose I need to simulate 10 times one variable and I want
to fi
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