Displaying 20 results from an estimated 2000 matches similar to: "quantile regression / problems calling nlrq from inside other functions"
2008 Jan 16
1
nlrq coefficients querry
I have been quantreg library for a number of projects but have just hit a
snag. I am using nlrq to examine an asymptotic relationship between 2
variables at the 99th percentile. It performs as expected, however when I
try to extract the coefficients along with se and significance I am running
into problems. The problem is that for the nlrq regression Dat.nlrq,
summary(Dat.nlrq) reports a different
2011 Oct 16
1
nlrq {quantreg}
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 <- nlrq(y ~ exp(x), tau=0.5)
I have the following error: Error in match.call(func, call = cll) :
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),
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 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,
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
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
2004 May 06
1
sporadic errors with nlrq() / optim()
Dear List,
Apologies if this is a known problem ... I wasn't able to find it on the bug
list, but it is a problem that does not seem to occur with a MAC build of R
2.0, so perhaps this problem has already been addressed for the future.
I am getting *sporadic* errors when refitting the same model to the same
data set, using nlrq() in the nlrq package. The algorithm is not stochastic,
so I
2003 Nov 20
0
Re: nlrq problem
Johannes,
You can minimize an model expression by just putting the ~ on the left
and everything else on the righthand side, but I don't think that this
is really what you want. In the NLS expression this would ignore the
jacobian of the transformation from errors to response, and in nlrq
there is the same problem, however you can adjust for the jacobian
by rescaling by the geometric mean of
2010 Mar 30
1
nlrq parameter bounds
Hi there,
Can anyone please tell me if it is possible to limit parameters in nlrq()
to 'upper' and 'lower' bounds as per nls()? If so how??
Many thanks in advance
2008 Aug 11
1
variance covariance matrix of parameter estimate using nlrq
In "lm" command, we can use "vcov" option to get variance-covariance matrix. Does anyone know how to get variance-covariance matrix in nlrq?
Thanks,
Kate
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2006 Dec 29
0
What's meaning of the lambda in nlrq output
I used the nlrq function in the package "quantreg". There is a lambda in
the output when I set trace=TRUE.
With different start point, the results are converged, but the last
lambda is different.
I want to know the meaning "lambda=1" and "lambda=0".
Many Thanks!
Examples of output
1. Where the last lambda=1:
108.6581 : 0.3 8.0
iter 0 value 108.658087
final
2003 Nov 20
3
nls, nlrq, and box-cox transformation
Dear r-help members
I posted this message already yesterday, but don't know whether it
reached you since I joined the group only yesterday.
I would like to estimate the boxcox transformed model
(y^t - 1)/t ~ b0 + b1 * x.
Unfortunately, R returns with an error message when I try to
perform this with the call
nls( I((y^t - 1)/t) ~ I(b0 + b1*x),
start = c(t=1,b0=0,b1=0), data = mydataframe)
2003 Sep 01
0
Quantile Regression Packages
I'd like to mention that there is a new quantile regression package
"nprq" on CRAN for additive nonparametric quantile regression estimation.
Models are structured similarly to the gss package of Gu and the mgcv
package of Wood. Formulae like
y ~ qss(z1) + qss(z2) + X
are interpreted as a partially linear model in the covariates of X,
with nonparametric components defined as
2004 Mar 25
1
factor based on pattern match ?
Hello,
is't possible to specify pattern in levels ?
> y=c("ff","f","m","mm","fm","mf","ffm","mmf","mmm","fff");
> factor(y)
[1] ff f m mm fm mf ffm mmf mmm fff
Levels: f ff fff ffm fm m mf mm mmf mmm
I want to specify levels using regexp ("f.*","m.*") or use
2004 Jan 23
1
Problem with hasArg() using R-files
Please do give reproducible example. The code you gave, which you claimed
`works correctly' doesn't:
> SDT.Optim <- function(crit = NULL, Hess = F)
+ {
+ q <- length(par); x <- data
+ if(hasArg(crit))
+ cat("\n Crit present\n")
+ else
+
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
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