Re: [R] quantile regression: warning message

: R-help@r-project.org Subject: Re: [R] quantile regression: warning message see the output from the quantreg FAQ: FAQ() especially point 2. url:www.econ.uiuc.edu/~rogerRoger Koenker emailrkoen...@uiuc.eduDepartment of Economics vox: 217-333-4558

Re: [R] quantile regression: warning message

see the output from the quantreg FAQ: FAQ() especially point 2. url:www.econ.uiuc.edu/~rogerRoger Koenker emailrkoen...@uiuc.eduDepartment of Economics vox: 217-333-4558University of Illinois fax: 217-244-6678Urba

Re: [R] Quantile Regression without intercept

me implies 0 expenditure, then all (quantile) Engel curves pass through the origin and one might want to impose this. On the other hand maybe not... > From: Roger Koenker > Sent: ‎06-‎10-‎2015 07:09 PM > To: Lorenz, David > Cc: r-help@r-project.org > Subject: Re: [R] Quantile R

Re: [R] Quantile Regression without intercept

e that. > > > > > > > >> Date: Mon, 5 Oct 2015 21:14:04 +0530 > >> From: Preetam Pal > >> To: stephen sefick > >> Cc: "r-help@r-project.org" > >> Subject: Re: [R] Quantile Regression without intercept > >> Mess

Re: [R] Quantile Regression without intercept

To wit: > y <- rnorm(100, 10) > x <- 1:100 > sum(resid(lm(y~x))) [1] 1.047773e-15 > sum(resid(lm(y~x-1))) [1] 243.0583 and replicating this should convince you that the mean residual really is not zero in the severely misspecified model with no intercept. (This has to do with the fact that resi

Re: [R] Quantile Regression without intercept

ate: Mon, 5 Oct 2015 21:14:04 +0530 > >> From: Preetam Pal > >> To: stephen sefick > >> Cc: "r-help@r-project.org" > >> Subject: Re: [R] Quantile Regression without intercept > >> Message-ID: <56129a41.025f440a.b1cf4.f...@mx.google.com> > &g

Re: [R] Quantile Regression without intercept

>> Date: Mon, 5 Oct 2015 21:14:04 +0530 > >> From: Preetam Pal > >> To: stephen sefick > >> Cc: "r-help@r-project.org" > >> Subject: Re: [R] Quantile Regression without intercept > >> Message-ID: <56129a41.025f440a.b1cf4.f...@mx.goo

Re: [R] Quantile Regression without intercept

etam Pal >> To: stephen sefick >> Cc: "r-help@r-project.org" >> Subject: Re: [R] Quantile Regression without intercept >> Message-ID: <56129a41.025f440a.b1cf4.f...@mx.google.com> >> Content-Type: text/plain; charset="UTF-8" >> >> Ye

Re: [R] Quantile Regression without intercept

:04 +0530 > From: Preetam Pal > To: stephen sefick > Cc: "r-help@r-project.org" > Subject: Re: [R] Quantile Regression without intercept > Message-ID: <56129a41.025f440a.b1cf4.f...@mx.google.com> > Content-Type: text/plain; charset="UTF-8" > > Ye

Re: [R] Quantile Regression without intercept

Yes..it works. Thanks 😃 -Original Message- From: "stephen sefick" Sent: ‎05-‎10-‎2015 09:01 PM To: "Preetam Pal" Cc: "r-help@r-project.org" Subject: Re: [R] Quantile Regression without intercept I have never used this, but does the formula inter

Re: [R] Quantile Regression without intercept

I have never used this, but does the formula interface work like lm? Y~X-1? On Mon, Oct 5, 2015 at 10:27 AM, Preetam Pal wrote: > Hi guys, > > Can you instruct me please how to run quantile regression without the > intercept term? I only know about the rq function under quantreg package, > but i

Re: [R] Quantile Regression without intercept

as for lm() or any other linear model fitting…. rq( y ~ x - 1, … ) url:www.econ.uiuc.edu/~rogerRoger Koenker emailrkoen...@uiuc.eduDepartment of Economics vox: 217-333-4558University of Illinois fax: 217-244-6678U

Re: [R] Quantile regression model with nonparametric effect and interaction

loop therefore does not really help... -Original Message- From: Roger Koenker [mailto:rkoen...@illinois.edu] Sent: Donnerstag, 11. Juni 2015 15:33 To: Waltl, Sofie (sofie.wa...@uni-graz.at) Cc: r-help@r-project.org Subject: Re: [R] Quantile regression model with nonparametric effec

Re: [R] Quantile regression model with nonparametric effect and interaction

The main effect trend seems rather dangerous, why not just estimate the f’s in a loop? url:www.econ.uiuc.edu/~rogerRoger Koenker emailrkoen...@uiuc.eduDepartment of Economics vox: 217-333-4558University of Illinois fax: 217-244-6678

Re: [R] 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 co

Re: [R] Quantile regression for binary choice and heckit

This is a bit like asking how should I tweak my sailboat so I can explore the ocean floor. url:www.econ.uiuc.edu/~rogerRoger Koenker emailrkoen...@uiuc.eduDepartment of Economics vox: 217-333-4558University of Illinois fax: 217-244-6678

Re: [R] quantile regression using copulas

Hi Marius, I have tried debugging the qua.regressCOP2 function. The error I'am getting is: "Error in cop(u, v + delv, ...) : unused argument(s) (v + delv)". Unable to decipher it. And have mailed to william.asquith at ttu.edu>. Thanks indu -- View this message in context: http://r.789695.n4

Re: [R] quantile regression using copulas

Please note: 1) your example is not working in the way you provided it (see http://www.minimalbeispiel.de/mini-en.html) 2) you receive a warning, not an error 3) I'd try and debug qua.regressCOP2 to see why the warning appears 4) in case 3) does not help, contact the maintainer of copBasic (Willia

Re: [R] Quantile Regression - Testing for Non-causalities in quantiles

Take a look at demo(Mel) in the quantreg package. Roger Koenker rkoen...@illinois.edu On Jul 14, 2012, at 6:55 AM, stefan23 wrote: > Dear all, > I am searching for a way to compute a test comparable to Chuang et al. > ("Causality in Quantiles and Dynamic Stock > Return-Volume Relations"). Th

Re: [R] Quantile regression: Discrepencies Between optimizer and rq()

Optim() by default is using Nelder-Mead which is an extremely poor way to do linear programming, despite the fact that ?optim says that: "It will work reasonably well for non-differentiable functions."I didn't check your coding of the objective function fully, but at the very least you sho

Re: [R] quantile regression: out of memory error

Using tau = -1 is causing rq() to try and estimate all possible quantiles and store the results. With 11253 observations this would be a formidable feat. Try estimating the model with say tau = 1:99/100 to give a more tractable number of estimates. Brian Brian S. Cade, PhD U. S. Geological

Re: [R] quantile regression: out of memory error

Paul, Yours is NOT a large problem, but it becomes a large problem when you ask for ALL the distinct QR solutions by specifying tau = -1. You probably don't want to see all these solutions, I suspect that only tau = 1:19/20 or so would suffice. Try this, and see how it goes. Roger url:ww

Re: [R] quantile regression: out of memory error

Koenker [mailto:rkoen...@uiuc.edu] Sent: Monday, July 11, 2011 12:48 PM To: Prew, Paul Cc: r-help@r-project.org help Subject: Re: [R] quantile regression: out of memory error Paul, Yours is NOT a large problem, but it becomes a large problem when you ask for ALL the distinct QR solutions by

Re: [R] Quantile Regression and R

Pls disregard...I have it figured out. Thank you. Regards, Peter D. Sheldrick Hartford Financial Services Group > _ > From: Sheldrick, Peter (Specialty Casualty UW Support) > Sent: Friday, April 08, 2011 9:53 AM > To: 'r-help@R-project.

Re: [R] Quantile Regression and R

Dear Peter, Quantile regression is a nice tool but one that requires some statistical training in order to use it and interpret the results properly. I suggest backing up a bit. Frank Sheldrick, Peter (Specialty Casualty UW Support) wrote: > > Sir or Madam: > > I am new to R and the

Re: [R] Quantile regression (rq) and complex samples

You could use the survey package to run the bootstrapping, if you mean the Rao & Wu bootstrap that samples n-1 of n PSUs in each replicate. Set up a survey design object with bootstrap replicate weights: use svrepdesign() if you already have replicate weights, use svydesign() and then as.svrepdesi

Re: [R] Quantile Regression: Extracting Residuals

Try looking here: ?rq.object ?residuals R has excellent documentation that can answer many such questions with less than a minute of reading. -- Jonathan P. Daily Technician - USGS Leetown Science Center 11649 Leetown Road Kearneysville WV, 25430 (304) 724-448

Re: [R] quantile regression

Thank you all for the explanation! Best, Julia > Date: Thu, 7 Oct 2010 22:37:32 +1100 > Subject: Re: [R] quantile regression > From: michael.bedw...@gmail.com > To: martyn.b...@nag.co.uk > CC: julia.l...@hotmail.co.uk; r-help@r-project.org > > Hi Julia, > &

Re: [R] quantile regression

Hi Julia, In addition to Martyn's answer and David's friendly post I'd just add that it's not a good idea to call a variable "c" since the function of that name is so often used in R. Michael On 7 October 2010 22:28, Martyn Byng wrote: > Hi, > > Your code is of the form > > for (i in 1:nsim) {

Re: [R] quantile regression

On Oct 7, 2010, at 6:40 AM, Julia Lira wrote: 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

Re: [R] quantile regression

Hi, Your code is of the form for (i in 1:nsim) { ## Do something that generates variable qf05 M <- coeff(qf05) } This means that you are overwriting the variable M at each iteration and so when the loop has finished you only have the coefficients from the last simulation. There are lots of

Re: [R] quantile regression

,i] <- coef(qf05) } I am quite sure there is a mistake in the code: qf05 <- rq(formula = mresultb[,i] ~ mresultx[,i], tau=0.5) because it is just generating the coefficients for one simulation, not for 10 simulations. best, Julia Date: Thu, 7 Oct 2010 18:51:40 +0800 Subject: Re

Re: [R] Quantile Regression and Goodness of Fit

http://www.econ.uiuc.edu/~roger/research/R1/R1.html On Mon, Aug 23, 2010 at 2:15 PM, Steven Ranney wrote: > All - > > Does anyone know if there is a method to calculate a goodness-of-fit > statistic for quantile regressions with package quantreg? > Specifically, I'm wondering if anyone has imple

Re: [R] Quantile regression - violation of independence

This is not an R question, though you may receive help from this list. But you would probably do better posting on a statistical list, especially one focused on ecology. Bert Gunter Genentech Nonclinical Biostatistics -Original Message- From: r-help-boun...@r-project.org [mailto:r-help

Re: [R] Quantile Regression fixed effects model

Dear R-users, I am applying professor Koenker's code for fixed effect quantile regression. However, I need to bootstrap and cluster the standard errors in my fitted model. Assuming that I need to bootstrap then cluster the standard errors by s (the strata indicator in Prof. Koenker's code), what

Re: [R] Quantile Regression for Longitudinal Data. Warning message: In rq.fit.sfn

Dear Dimitris, I have exactly the same problem than you, Do you get some solution? Thanks, Lola Lola Gadea Profesora titular de Economía Aplicada/Lecturer in Applied Economics Universidad de Zaragoza/University of Zaragoza (Spain) lga...@unizar.es

Re: [R] Quantile Regression fixed effects model

see: http://www.econ.uiuc.edu/~roger/research/panel/rq.fit.panel.R url:www.econ.uiuc.edu/~rogerRoger Koenker email[EMAIL PROTECTED]Department of Economics vox: 217-333-4558University of Illinois fax: 217-244-6678Champaign,

Re: [R] Quantile Regression for Longitudinal Data:error message

If you are going to insist on doing such things you will have to learn to read the documentation. In this case if you do a traceback() you will see that the error is occurring in rq.fit.slm and when you do ?rq.fit.slm you will see that there are several storage sizes that can

Re: [R] Quantile Regression for Longitudinal Data. Warning message: In rq.fit.sfn

This is a little esoteric for R-help. As the posting guide says, you should write the package maintainer with this sort of question. Without the data it is difficult to judge what is happening, a couple of possibilities are: o all is well and warning just conveys an exaggerated s

Re: [R] quantile regression: plotting coefficients on only one variable (rq)

Hi Michael, It's in the manual: ?plot.summary.rqs plot(summary(rq(..., tau=c(...)), parm = x1, ...) Regards, Mark. Michael Faye wrote: > > Dear all. > > I have a question on plotting the coefficients from a series of > mutivariate > quantile regressions. The following code plots the coeff

Re: [R] Quantile regression with complex survey data

enter 2150 Centre Ave., Bldg. C Fort Collins, CO 80526-8818 email: [EMAIL PROTECTED] tel: 970 226-9326 "Stas Kolenikov" <[EMAIL PROTECTED]> Sent by: [EMAIL PROTECTED] 08/20/2008 01:14 PM To "Cheng, Yiling (CDC/CCHP/NCCDPHP)" <[EMAIL PROTECTED]> cc r-help@r

Re: [R] Quantile regression with complex survey data

You can get point estimates by supplying the sampling weights as weights to the quantile regression functions in Roger Koenker's quantreg package. This is useful for smoothing (with the rqss() function; it is not clear how useful it is for straight line regression. You should get valid inte

Re: [R] Quantile regression with complex survey data

On Wed, Aug 20, 2008 at 8:12 AM, Cheng, Yiling (CDC/CCHP/NCCDPHP) <[EMAIL PROTECTED]> wrote: > I am working on the NHANES survey data, and want to apply quantile > regression on these complex survey data. Does anyone know how to do > this? There are no references in technical literature (thinking,

Re: [R] quantile regression estimation results

The canonical answer is: It is R, so everything is possible. Sounds like you need to read what is produced by ?summary.rq carefully. url:www.econ.uiuc.edu/~rogerRoger Koenker email [EMAIL PROTECTED] Department of Economics vox:217-333-45

Re: [R] Quantile regression

> I am trying to perform quantile regression analysis to analyse my work. I > could install the R package in windows xp. Now I am struggling > for the next work.I have *marks of students at the university > examinations*( say response variable Y) and their > *entrance examination marks* ( Independ

Re: [R] Quantile Regression Question

Package questions to package maintainers please. "non-positive fis" is not an error, it is a warning -- if the number of negative fis is large relative to the sample size then there is some reason to doubt the plausibility of the specification of the model specified by the rq formula.