similar to: R memory issue / quantreg

Dear all, I want to use the "rearrange" command which is based on Chernozhukov et al paper and is included in the quantreg package. So, I run a quantile regression in which I included dummy variables for state and years in order to estimate the respective fixed effects quantile regression. The problems are the followings: 1. At example that is stated in the help****, I don't

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 ------------

Dear all, I know that my question is somewhat special but I tried several times to solve the problems on my own but I am unfortunately not able to compute the following test statistic using the quantreg package. Well, here we go, I appreciate every little comment or help as I really do not know how to tell R what I want it to do^^ My situation is as follows: I have a data set containing a

A new version of the quantile regression package (quantreg 3.09) is now available on CRAN. The new features include: 1. a new fitting method "fnc" for rq() which allow the call to specify linear inequality constraints on the coefficients. 2. an anova() function for rq objects that implements several F-like tests for quantile regression models at a given quantile, and other F-like

Dear all, I am using the "rq.fit.hogg" function from the "quantreg" package. I have two problems with it. First (less importantly), it gives an error at its default values with error message "Error in if (n2 != length(r)) stop("R and r of incompatible dimension") : argument is of length zero". I solve this by commenting four lines in the code. I.e. I

Hello all, I would like to compute a quantile regression using rq (from the quantreg package), while keeping one of the coefficients fixed. Is it possible to set an offset for rq in quantreg? (I wasn't able to make it to work) Thanks, Tal ----------------Contact Details:------------------------------------------------------- Contact me: Tal.Galili at gmail.com |? 972-52-7275845 Read me:

Dear all How can I obtain the data from the function "rearrange" in package quantreg More especifically, based on the example below (available in the help of the rearrange function), how can I access the data generated by "rearrange(zp)" ? data(engel) z <- rq(foodexp ~ income, tau = -1,data =engel) zp <-

Dear all, My question might be more of a statistics question than a question on R, although it's on how to apply the 'quantreg' package. Please accept my apologies if you believe I am strongly misusing this list. To be very brief, the problem is that I have data on only a random draw, not all of doctors' patients. I am interested in the, say, median number of patients of

Hi all, I'm having some troubles with the Quantreg package. I am using R version 2.10.0, and have downloaded the most recent version of Quantreg (4.44) and SparseM (0.83 - required package). However, when I try to run an analysis (e.g. fit1<-rq(y~x, tau=0.5)) I get an error message saying that the function "rq" could not be found. I get the same message when I try to search

Hi I am using the quantreg package for median regression for a large series of subsets of data. It works fabulously for all but one subset. When it reaches this subset, R takes the command and never responds. I end up having to kill R and restart it. It appears to be something with the particular data subset, but I can't pinpoint the problem. Here are some details Operating system:

Hi, I am trying to use quantile regression to perform weighted-comparisons of the median across groups. This works most of the time, however I am seeing some odd output in summary(rq()): Call: rq(formula = sand ~ method, tau = 0.5, data = x, weights = area_fraction) Coefficients: Value Std. Error t value Pr(>|t|) (Intercept) 45.44262 3.64706 12.46007

Hi all, I'm using quantreg rq() to perform quantile regression on a large data set. Each record has 4 fields and there are about 18 million records in total. I wonder if anyone has tried rq() on a large dataset and how long I should expect it to finish. Or it is simply too large and I should subsample the data. I would like to have an idea before I start to run and wait forever. In addition,

Hi Folks, I've got a question regarding the 'quantreg' package maintained by Roger Koenker: I tried to produce LaTeX tables using the longtable and dcolumn options as decribed in the manual, but the function latex() doesn't seem to react on _any_ other options than 'digits' and 'transpose'. To reproduce these results the following minimal example may be used:

Hi All, I'm still having significantly difficulty getting the quantreg library running in R. I'm running R on MEPIS using the debs created by Dirk Eddelbuettel and placed in apt testing. When I try to install quantreg using the install.packages() function it fails with: /usr/bin/ld: cannot find -lblas-3 Dirk was nice enough to send me a .deb for quantreg which installs without

He folks=) I want to check whether a coefficient has an impact on a quantile regression (by applying the sup-wald test for a given quantile range [0.05,0.95]. Therefore I am doing the following calculations: a=0; for (i in 5:95/100){ fitrestricted=rq(Y~X1+X2,tau=i) tifunrestrited=rq(Y~X1+X2+X3,tau=i) a[i]=anova(fitrestricted,fitunrestricted)$table$Tn) #gives the Test-Value } supW=max(a) As anova

Hi All, I'm trying to install the quantreg library on my MEPIS box (debian-based linux). When I try >install.packages("quantreg") it fails to loads and errors with: /usr/bin/ld: cannot find -lblas-3. I tried installing a ton of packages to fix the missing part but the only thing I manage to do it cause problems with another shared library and had to re-install a couple of

Hi All, I'm trying to install the quantreg library on my MEPIS box (debian-based linux). When I try >install.packages("quantreg") it fails to loads and errors with: /usr/bin/ld: cannot find -lblas-3. I tried installing a ton of packages to fix the missing part but the only thing I manage to do it cause problems with another shared library and had to re-install a couple of

Dear all, I am having v.4.36 of Quantreg package and I noticed strange behaviour when weights were added. Could anyone please explain me what if the results are really strange or the behavioiur is normal. As an example I am using dataset Engel from the package and my own weights. x<-engel[1:50,1] y<-engel[1:50,2] w<-c(0.00123, 0.00050, 0.00126, 0.00183, 0.00036, 0.00100, 0.00122,

Full_Name: Edward Huang Version: 2.6.1 OS: Mac OS 10.5.1 Leopard Submission from: (NULL) (71.198.106.232) I'm trying to run quantile regression on my data. I just couldn't make it work. The same dataset ran okay on STATA 10, tho. Would you please take a look at it? Here is the error message: *** caught segfault *** address 0x3ff00008, cause 'memory not mapped' Traceback:

Quantreg package allows to plot the summary of models derived by quantile regression at different taus. The plot shows the parameters variation by varying taus: intercept and slope (for a linear model). Together with these values even confidence intervals may be plotted, based on the threshold given within the summary (e.g. alpha=0.01 equals 99% CI). However the graphic even plots the mean of