Displaying 20 results from an estimated 10000 matches similar to: "Interpreting Quantile Regression"
2011 Nov 19
1
wald test: compare quantile regression estimators from different samples
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 characteristic indeed affect the estimators. The problem in the test anova.rq is that the response variable
2012 Jul 17
1
Threshold Quantile Regression code CRASHES in R
I am working on a two stage threshold quantile regression model in R, and my aim is to estimate the threshold of the reduced-form equation (call it rhohat), and the threshold of the structural equation (call it qhat), in two stages. On the first stage, i estimate rhohat by quantile regression and obtain the fitted values. I use these fitted values to estimate qhat on the second stage. The code is
2009 Jun 09
1
Non-linear regression/Quantile regression
Hi,
I'm relatively new to R and need to do a quantile regression. Linear
quantile regression works, but for my data I need some quadratic function.
So I guess, I have to use a nonlinear quantile regression. I tried the
example on the help page for nlrq with my data and it worked. But the
example there was with a SSlogis model. Trying to write
dat.nlrq <- nlrq(BM ~ I(Regen100^2),
2008 Jan 01
2
Non-Linear Quantile Regression
Please,
I have a problem with nonlinear quantile regression.
My data shows a large variability and the quantile regression seemed perfect
to relate two given variables. I got to run the linear quantile regression
analysis and to build the graph in the R (with quantreg package). However, the
up part of my data dispersion seems a positive exponential curve, while the
down part seems a negative
2006 Jul 23
1
Warning Messages using rq -quantile regressions
I am a new to using quantile regressions in R. I have estimated a set of
coefficients using the method="br" algorithm with the rq command at various
quantiles along the entire distribution.
My data set contains approximately 2,500 observations and I have 7 predictor
variables. I receive the following warning message:
Solution may be nonunique in: rq.fit.br(x, y, tau = tau, ...)
2012 Jun 07
1
Quantile regression: Discrepencies Between optimizer and rq()
Hello Everyone,
I'm currently learning about quantile regressions. I've been using an
optimizer to compare with the rq() command for quantile regression.
When I run the code, the results show that my coefficients are consistent
with rq(), but the intercept term can vary by a lot.
I don't think my optimizer code is wrong and suspects it has something to do
with the starting
2006 Dec 02
2
nonlinear quantile regression
Hello, I?m with a problem in using nonlinear quantile regression, the
function nlrq.
I want to do a quantile regression o nonlinear function in the form
a*log(x)-b, the coefficients ?a? and ?b? is my objective. I try to use the
command:
funx <- function(x,a,b){
res <- a*log(x)-b
res
}
Dat.nlrq <- nlrq(y ~ funx(x, a, b), data=Dat, tau=0.25, trace=TRUE)
But a can?t solve de problem,
2008 Feb 06
1
Mixed models quantile regression
Dear R,
I have a question concerning quantile regression models.
I am using the quantile regression model to test the relationship between
abalone and the percentage cover of algae etc at different sites and depths.
An example is
fit<-rq(abalone~%coversessileinvertebrates+factor(Depth)+factor(Site),tau=0.7)
In this model depth is fixed and site is random. My question is, is it
possible
2004 Feb 04
1
Fitting nonlinear (quantile) models to linear data.
Hello.
I am trying to fit an asymptotic relationship (nonlinear) to some
ecological data, and am having problems. I am interested in the upper
bound on the data (i.e. if there is an upper limit to 'y' across a range
of 'x'). As such, I am using the nonlinear quantile regression package
(nlrq) to fit a michaelis mention type model.
The errors I get (which are dependant on
2006 Oct 25
1
Quantile Regression
Hi,
how is it possible to retrieve the corresponding tau value for each observed data pair (x(t) y(t), t=1,...,n) when doing a quantile regression like
rq.fit <- rq(y~x,tau=-1).
Thank you for your help.
Jaci
--
2008 Sep 23
1
quantile regression: plotting coefficients on only one variable (rq)
Dear all.
I have a question on plotting the coefficients from a series of mutivariate
quantile regressions. The following code plots the coefficients for each
RHS variable x1 and x2. Is there a way to plot only the coefficients on x1?
In the data I am using, I have a large number of fixed effects and do want
to plot the coefficients on these fixed effects.
quant.plot <-
2011 Jul 11
3
quantile regression: out of memory error
Hello, I?m wondering if anyone can offer advice on the out-of-memory error I?m getting. I?m using R2.12.2 on Windows XP, Platform: i386-pc-mingw32/i386 (32-bit).
I am using the quantreg package, trying to perform a quantile regression on a dataframe that has 11,254 rows and 5 columns.
> object.size(subsetAudit.dat)
450832 bytes
> str(subsetAudit.dat)
'data.frame': 11253 obs.
2010 Oct 07
3
quantile regression
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 variable. I need to regress each column of mresultb on mresultx. My codes are the following:
2012 Jul 19
0
Quantile regression questions
Hi, everyone.
I have some questions about quantile regression in R.
I am running an additive quantile regression first for a complete matrix and then with some selected rows.
I am doing the following:
datos <-read.table("Regresion multiple.txt",header=T)
Fit<-rqss(datos$campings ~datos$Cobarbogrupo+datos$CobSDgrupo+datos$Areadecultivosgrupo, tau=0.9)
summary.rq(Fit)
#The
2018 Feb 23
0
Quantile regression with some parameters fixed across tau..
Hi,
I would like to fit the following model with quantile regression:
y ~ alpha + beta
where both alpha and beta are factors. The conceptual model I have in my
head is that alpha is a constant set of values, that should be independent
of the quantile, tau and that all of the variability arises due to beta. If
I just fit the model using the quantreg package like so:
mdl <- rq( y ~ alpha
2011 Aug 23
3
Change Variable Labels in Quantile Plot
I have spent hours on this ---looked through the quantreg manual and r-help site--- still couldn't figure out the answer. Can someone please help me on this?
I plot the result from quantile regression and want to change the variable labels:
temp<-rq(dep~inc+age50, data=newdata, tau=1:9/10)
temp2<-plot(summary(temp))
dimnames(temp2)[[1]]<-c("Intercept", "Per Capita
2012 Feb 13
1
non linear quantile regression - Median not plotting where it should
Hi,
I'm attempting to calculate the 0.25 and 0.97 quantiles for tree height (0-50 meters) against tree age (0-300 years) and I am running into some difficulty with the plotted grafic. I've run the examples in the quantreg help and can get those to work properly and by plugging in my data I can also get the lines plotted on my dataset. Unfortunately I'm running into a problem with the
2013 Jun 29
0
Quantile Regression/(package (quantreg))
Mike,
Do something like:
require(rms)
dd <- datadist(mydatarame); options(datadist='dd')
f <- Rq(y ~ rcs(age,4)*sex, tau=.5) # use rq function in quantreg
summary(f) # inter-quartile-range differences in medians of y (b/c tau=.5)
plot(Predict(f, age, sex)) # show age effect on median as a continuous
variable
For more help type ?summary.rms and ?Predict
Frank
------------
2009 May 31
1
warning message when running quantile regression
Hi All,
I am running quantile regression in a "for loop" starting with 1
variable and adding a variable at a time reaching a maximum of 20
variables.
I get the following warning messages after my "for" loop runs. Should I
be concerned about these messages? I am building predictive models and
am not interested in inference.
Warning messages:
1: In
2011 Jan 11
1
Confidence interval on quantile regression predictions
I am using the quantreg package to build a quantile regression model and
wish to generate confidence intervals for the fitted values.
After fitting the model, I have tried running predict() and
predict.rq(), but in each case I obtain a vector of the fitted values
only.
For example:
library(quantreg)
y<-rnorm(50,10,2)
x<-seq(1,50,1)