similar to: Quantile Regression: Measuring Goodness of Fit

Displaying 20 results from an estimated 4000 matches similar to: "Quantile Regression: Measuring Goodness of Fit"

2010 Aug 23
2
Quantile Regression and Goodness of Fit
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 implemented the goodness-of-fit process developed by Koenker and Machado (1999) for R? Though I have used package quantreg in the past, I may have overlooked this function, if it is included. Citation: Koenker, R. and
2007 Nov 29
1
Testing normality
Hi, I'm doing kolmogorv-smirnov test but I don't know what conclusions to take, I want to know if my data has a normal distribution: > ks.test(dados1,"pnorm") One-sample Kolmogorov-Smirnov test data: dados1 D = 0.972, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: cannot compute correct p-values with ties in: ks.test(dados1,
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
2012 Jul 14
1
Quantile Regression - Testing for Non-causalities in quantiles
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"). The aim of this test is to check wheter the coefficient of a quantile regression granger-causes Y in a quantile range. I have nearly computed everything but I am searching for an estimator of the density of the distribution at several
2024 Sep 06
1
effects() extractor for a quantile reqression object: error message
I'm using quantreg package version 5.98 of 24 May 2024, in R 4.4.1 on Linux Mint. The online documentation for quantreg says, in part, under the description of the rq.object, "The coefficients, residuals, and effects may be extracted by the generic functions of the same name, rather than by the $ operator." I create an rq object for the 0.9 quantile, called qm.9 effects(qm.9)
2010 Jan 25
2
Quantile loess smother?
Hello all, I wish to fit a loess smother to a plot of Y`X, but in predicting the 95% quantile. Something that will be a combination of what rq (package quantreg} does, with loess. Is there a function/method for doing this? Thanks, Tal ----------------Contact Details:------------------------------------------------------- Contact me: Tal.Galili@gmail.com | 972-52-7275845 Read me:
2004 Jun 15
1
fit.mult.impute and quantile regression
I have a largish dataset (1025) with around .15 of the data missing at random overall, but more like .25 in the dependent variable. I am interested in modelling the data using quantile regression, but do not know how to do this with multiply imputed data (which is what the dataset seems to need). The original plan was to use qr (or whatever) from the quantreg package as the 'fitter'
2009 May 29
3
Quantile GAM?
R-ers: I was wondering if anyone had suggestions on how to implement a GAM in a quantile fashion? I'm trying to derive a model of a "hull" of points which are likely to require higher-order polynomial fitting (e.g. splines)-- would quantreg be sufficient, if the response and predictors are all continuous? Thanks! --j
2014 Sep 30
5
Clasificacion de individuos
Estimados apañeRos: La duda o propuesta que os voy a plantear es a la vez metodológica y relacionada con R. Me encuentro trabajando con tres variables que son el resultado de un computo de porcentajes. Me explico, se toma una muestra de n casos (unos 6.500 aprox) pertenecientes a i individuos (unos 230 aprox) en la que se comprueba si un determinado evento ha ocurrido o no, anotándose 1 en
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)
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.
2007 Nov 11
1
Non-crossing Nonparametric quantile regressions
I've been looking for ways to calculate a large number (100) of non-crossing Nonparametric quantile regressions on large populations (1000+). Can the quantreg package in R ensure the non-crossing property? If not, do you know any alternative? Thank you, Paulbegc -- View this message in context:
2024 Sep 06
1
Fwd: effects() extractor for a quantile reqression object: error message
Apologies, forgot to copy R-help on this response. Begin forwarded message: From: Roger Koenker <rkoenker at illinois.edu> Subject: Re: [R] effects() extractor for a quantile reqression object: error message Date: September 6, 2024 at 8:38:47?AM GMT+1 To: "Christopher W. Ryan" <cryan at binghamton.edu> Chris, This was intended to emulate the effects component of lm()
2006 Feb 05
1
how to extract predicted values from a quantreg fit?
Hi, I have used package quantreg to estimate a non-linear fit to the lowest part of my data points. It works great, by the way. But I'd like to extract the predicted values. The help for predict.qss1 indicates this: predict.qss1(object, newdata, ...) and states that newdata is a data frame describing the observations at which prediction is to be made. I used the same technique I used
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
2008 Jul 10
1
quantile regression estimation results
Dear list, I'm using the quantreg package for quantile regression. Although it's fine, there're is some weird behavior a little bit difficult to understant. In some occasions, the regression results table shows coefficients, t-statistics, standard errors and p-values. However, in other occasions it shows only coefficients and confidence intervals. Therefore, the question is... Is
2009 Jul 30
1
Selecting Bootstrap Method for Quantile Regression
The help page and vignette for summary.rq(quantreg) mention that there are three different bootstrap methods available for the se="bootstrap" argument, but I can't figure out how to select a particular method. For example, if I want to use the "xy-pair bootstrap" how do I indicate this in summary.rq? Tom -- View this message in context:
2011 Nov 05
2
linear against nonlinear alternatives - quantile regression
Dear all, I would like to know whether any specification test for linear against nonlinear model hypothesis has been implemented in R using the quantreg package. I could read papers concerning this issue, but they haven't been implemented at R. As far as I know, we only have two specification tests in this line: anova.rq and Khmaladze.test. The first one test equality and significance of
2009 May 08
1
Citing R/Packages Question
I used R and the quantreg package in a manuscript that is currently in the proofs stage. I cited both R and quantreg as suggested by citation() and noted the version of R and quantreg that I used in the main text as "All tests were computed with the R v2.9.0 statistical programming language (R Development Core 2008). Quantile regressions were conducted with the quantreg v4.27 package
2006 Jul 14
1
Error in Quantile Regression - Clear Message
Dear Users, I loaded my dataset as following: presu <- read.table("C:/_Ricardo/Paty/qtdata_f.txt", header=TRUE, sep="\t", na.strings="NA", dec=".", strip.white=TRUE) dep<-presu[,3]; exo<-presu[,4:92]; When I try: rq(dep ~ exo, ...) or mle.stepwise(dep ~ exo, ...) I got the same error: > rq(dep ~ exo) Error in model.frame(formula, rownames,