# similar to: Quantile regression with some parameters fixed across tau..

Displaying 20 results from an estimated 1938 matches similar to: "Quantile regression with some parameters fixed across tau.."

2017 Jun 19
0
quantreg::rq.fit.hogg crashing at random
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
2018 Apr 07
1
Fast tau-estimator line does not appear on the plot
You need to pay attention to the documentation more closely. If you don't know what something means, that is usually a signal that you need to study more... in this case about the difference between an input variable and a design (model) matrix. This is a concept from the standard linear algebra formulation for regression equations. (Note that I have never used RobPer, nor do I regularly
2018 Apr 06
1
Fast tau-estimator line does not appear on the plot
R-experts, I have fitted many different lines. The fast-tau estimator (yellow line) seems strange to me?because this yellow line is not at all in agreement with the other lines (reverse slope, I mean the yellow line has a positive slope and the other ones have negative slope). Is there something wrong in my R code ? Is it because the Y variable is 1 vector and should be a matrix ? Here is the
2018 Mar 31
1
Fast tau-estimator line does ot appear on the plot
Dear R-experts, Here below my reproducible R code. I want to add many straight lines to a plot using "abline" The last fit (fast Tau-estimator, color yellow) will not appear on the plot. What is going wrong ? Many thanks for your reply. ########## Y=c(2,4,5,4,3,4,2,3,56,5,4,3,4,5,6,5,4,5,34,21,12,13,12,8,9,7,43,12,19,21)
2013 Jun 29
0
Re: 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
2018 Mar 31
2
Fast tau-estimator line does ot appear on the plot
On 31/03/2018 11:57 AM, varin sacha via R-help wrote: > Dear R-experts, > > Here below my reproducible R code. I want to add many straight lines to a plot using "abline" > The last fit (fast Tau-estimator, color yellow) will not appear on the plot. What is going wrong ? > Many thanks for your reply. > It's not quite reproducible: you forgot the line to
2004 Jul 19
3
why won''t rq draw lines?
I''ve been trying to draw quantile linear regression lines across a scatterplot of my data using attach(forrq) plot(PREGNANT,DAY8,xlab="pregnant EPDS",ylab="postnatal EPDS",cex=.5) taus <- c(.05,.1,.25,.75,.9,.95) xx <- seq(min(PREGNANT),max(PREGNANT),100) for(tau in taus){ f <- coef(rq(DAY8~PREGNANT,tau=tau)) yy
2011 Sep 27
1
Is there a "latex" summary function in the quantreg package for just 1 tau?
Hello dear R help members, I wish to get a nice LaTeX table for a rq object. Trying to use the functions I found so far wouldn''t work. I can start opening the functions up, but I am wondering if I had missed some function which is the one I should be using. Here is an example session for a bunch of possible errors: (Thanks) data(stackloss) y <- stack.loss x <- stack.x
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'':
2018 May 24
2
Problem with adding a raster and a brick
Hi, I seem to be having a problem adding the following two raster objects together - one is a rasterLayer, the other is a rasterBrick. The extent, resolution, and origin are the same, so according to my understand it should work. The objects look like so: > obs.clim class : RasterLayer dimensions : 60, 200, 12000 (nrow, ncol, ncell) resolution : 0.5, 0.5 (x, y) extent : -70,
2018 Jun 01
0
Problem with adding a raster and a brick
This is now fixed in development on RForge, you can try it out by installing from there, or from the Github mirror with devtools::install_github("rforge/raster/pkg/raster"). (To get fixes into raster email the maintainer directly - you might not get a response but it'll be addressed). Cheers, Mike. On Thu, 24 May 2018 at 20:08 Michael Sumner <mdsumner at
2018 May 22
1
Bootstrap and average median squared error
Hello, If you want to bootstrap a statistic, I suggest you use base package boot. You would need the data in a data.frame, see how you could do it. library(boot) bootMedianSE <- function(data, indices){ d <- data[indices, ] fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d) ypred <- predict(fit) y <- d\$crp median(y - ypred)^2 } dat <-
2009 May 18
2
Overlay two quantreg coefficients plots
Dear R-mailing list, I would like to overlay to two quantreg coefficients plots. I have plot(summary(rq(ff~tipo,tau = 1:49/50,data=Spilldata))) plot(summary(rq(ff~tipo,tau = 1:49/50,data=Spilldata1))) Is there a possibility to display the two in the same graph? Thank you so much!!! Christian [[alternative HTML version deleted]]
2018 May 22
1
Bootstrap and average median squared error
I forgot, you should also set.seed() before calling boot() to make the results reproducible. Rui Barradas On 5/22/2018 10:00 AM, Rui Barradas wrote: > Hello, > > If you want to bootstrap a statistic, I suggest you use base package boot. > You would need the data in a data.frame, see how you could do it. > > > library(boot) > > bootMedianSE <-
2012 May 28
2
R quantreg anova: How to change summary se-type
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
2011 Jan 31
0
Function rearrange (quantreg)
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 <-
2011 Jan 11
1
Problems producing quantreg-Tables
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
2018 Apr 13
0
cvTools for 2 models not working
Dear R-experts, I am trying to do cross-validation for different models using the cvTools package. I can't get the CV for the "FastTau" and "hbrfit". I guess I have to write my own functions at least for hbrfit. What is going wrong with FastTau ? Here below the reproducible example. It is a simple toy example (not my real dataset) with many warnings, what is important to
2010 Jan 07
3
Quantreg - ''could not find function"rq"''
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
2018 May 21
1
Bootstrap and average median squared error
Dear R-experts, I am trying to bootstrap (and average) the median squared error evaluation metric for a robust regression. I can't get it. What is going wrong ? Here is the reproducible example. ############################# install.packages( "quantreg" ) library(quantreg) crp <-c(12,14,13,24,25,34,45,56,25,34,47,44,35,24,53,44,55,46,36,67) bmi