search for: robust

Dear R-Users: I am trying to find the robust (or sandwich) estimates of the standard error of fixed effects parameter estimates using the package "lmer2". In model-1, I used "robust=TRUE" on the other, in model-2, I used "robust=FALSE". Both models giving me the same estimates. So my question is, does the robust...

Can anyone comment or point me to a discussion of the pros and cons of robust regressions, vs. a more "manual" approach to trimming outliers and/or "normalizing" data used in regression analysis?

One of my colleagues has a data set from a two-level nested design from which we would like to estimate variance components. But we'd like some idea of what the inevitable outliers are doing, so we were looking for something in R that uses robust (eg Huber) treatment and returns robust estimates of variance. Nothing in my collection of R robust estimation packages (robust, robustbase and MASS being the obvious three) or on the Robust task view seems to cover this, though it's entirely possible I've missed something. Any pointers...

I have two regressions to perform - one with a metric DV (-3 to 3), the other with an ordered DV (0,1,2,3). Neither normal distribution not homoscedasticity is given. I have a two questions: (1) Some sources say robust regression take care of both lack of normal distribution and heteroscedasticity, while others say only of normal distribution. What is true? (2) Are there ways of using robust regressions with ordered data, or is that only possible for metric DVs? Thanks Torvon [[alternative HTML version deleted...

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Hi. I'm checking into robust methods for principal components analysis. There seem to be several floating around. I'm currently focusing my attention on a method of Hubert, Rousseeuw, and Vanden Branden (http://wis.kuleuven.be/stat/Papers/robpca.pdf) mainly because I'm familiar with other work by Rousseeuw and Hu...

Hi all, I have probably a basic question, but I can't seem to find the answer in the literature or in the R-archives. I would like to do a robust ANCOVA (using either rlm or lmRob of the MASS and robust packages) - my response variable deviates slightly from normal and I have some "outliers". The data consist of 2 factor variables and 3-5 covariates (fdepending on the model). However, the variance between my groups is not equal and...

Hi, I'm trying to use Robust non-linear regression to fit dose response curves. Maybe I didnt look good enough, but I dind't find robust methods for NON linear regression implemented in R. A method that looked good to me but is unfortunately not (yet) implemented in R is described in http://www.graphpad.com/articles/Robus...

...two different models in the framework of Cox proportional hazards regression models. On Rsitesearch and google I don't find a clear answer to my question. My R-Code (R version 2.9.0) coxph.fit0 <- coxph(y ~ z2_ + cluster(as.factor(keys))+ strata(stratvar_), method="breslow" ,robust=T ) coxph.fit1 <- coxph(y ~ z_ + cluster(as.factor(keys))+ strata(stratvar_), method="breslow" ,robust=T ) # marker and covariates # Analysis of Devaince table coxph.aov <- anova(coxph.fit0 , coxph.fit1, test="Chisq") In the single models coxph.fit0 and coxph.f...

Hi, i. After estimating some coefficients using robust regression with rlm() or lqs(), I wonder if there exist some measures of the goodness-of-fit as those for standard linear model(R2)... or evenly if it's a statistics non-sense to look for since I do not find any mention of that in differents chapters on robust and resistant regression or in sev...

Hi, I am using robust regression, i.e. model.robust<-ltsreg(MXD~ORR,data=DATA). My question:- is there any way to determine the Robust Multiple R-Squared (as returned in the summary output in splus)? I found an equivalent model in the rrcov package which included R-square, residuals etc in it's list of components...

Good evening,I am Marta Colombo, student of "Politecnico di Milano". I'm studying Local Regression Techniques such as loess, smoothing splines and kernel smoothers. Choosing "symmetric" for the argument "family" in loess function it is possible to produce a robust estimate , in function smooth.spline and ksmooth I didn't find this possibility. Well, is there a way to produce a robust estimate using smoothing splines or kernel smoothers? And if the answer is no, why? I'm asking these questions because I need to know loess' advantages and disadvant...

...ut arguments in the code but the declaration wasn't declared with a void parameter list. It failed with an assertion that something was trying to ++ past the end of an ilist. I seem to remember Chris Lattner saying when he made the hand written AsmParser that it wasn't intended to be very robust but, searching the list, I can't find the post where he said it. That being said, is this worthy of a bug report? An error message from the AsmParser would be preferred over a seemingly unrelated assert. Cheers, --Sam Crow

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of optimally robust estimators; i.e., &quo...

----------------------------------------------------------------------------------------- Packages for the computation of optimally robust estimators ----------------------------------------------------------------------------------------- We would like to announce the availability on CRAN (with possibly a minor delay until on every mirror) of new versions of our packages for the computation of optimally robust estimators; i.e., &quo...

...he declaration wasn't > declared with a void parameter list. It failed with an assertion > that something was trying to ++ past the end of an ilist. > > I seem to remember Chris Lattner saying when he made the hand > written AsmParser that it wasn't intended to be very robust but, > searching the list, I can't find the post where he said it. That > being said, is this worthy of a bug report? An error message from > the AsmParser would be preferred over a seemingly unrelated assert. Please file a bug, it certainly should be "robust". Swit...

Hi, I have ove the robust standard error of an estimator but I don't know how to do this. The code for my regression is the following: reg<-lm(fsn~lctot) But then what do I need to do? -- Charlène Lisa Cosandier [[alternative HTML version deleted]]

...tios obtained by logistic regression analysis. Cox regression is used for time-to-event data. To obtain prevalence rates the time has to be constant. One of the problems of Cox regression is that the confidence intervals are overestimated. To correct this Barros & Hirakata recommend the use of robust variance estimates. How can R be used to calculate the prevalence ratios using Cox regression + robust variance estimates ? Thanks for your collaboration, Tomas Karpati MD The Michaelson Institute for Rehabilitation of Vision Hadassah Medical Organization

Dear list, I am slightly confused about how I can do the following in R. I want to perform robust multiple regression. I?ve used the Boot function in CAR package to find confidence intervals and standard errors. Inadition to these, I want to find the robust estimates for the F test and r-square. Finally, I would like to know the significance levels of bootstrap results. Below I explain my...

...teraction effect. The regular ANVOA is problematic, because (a) the sample sizes are very unbalanced, due to the group IV, (b) the homogeneity of variance is violated, and (c) the homogeneity of covariance is also violated. I wonder if R has a procedure to address this issue, either by some sort of Robust ANOVA procedure, or by some alternative tests? Thanks a lot. Jinyan Fan Assistant Professor Department of Psychology Hofstra University Hempstead, NY 11550 Work: 516-463-6349 [[alternative HTML version deleted]]