similar to: robust regression

Hi, so I don't speak computer and I have no idea what this code is telling the program to do, but I apparently need to be able to find and isolate influencial observations. Problem, I have no idea what the error means and where it may be from in the code. error I get is below the code { ## OLS results NameC<- lm(gpanew~female+female:lastinit+agenew+canadian+mom_ed+yearstudy) ## default:

Dear List-members, I found a strange behaviour in the lqs function. Suppose I have the following data: y <- c(7.6, 7.7, 4.3, 5.9, 5.0, 6.5, 8.3, 8.2, 13.2, 12.6, 10.4, 10.8, 13.1, 12.3, 10.4, 10.5, 7.7, 9.5, 12.0, 12.6, 13.6, 14.1, 13.5, 11.5, 12.0, 13.0, 14.1, 15.1) x1 <- c(8.2, 7.6,, 4.6, 4.3, 5.9, 5.0, 6.5, 8.3, 10.1, 13.2, 12.6, 10.4, 10.8, 13.1, 13.3, 10.4, 10.5, 7.7, 10.0, 12.0,

Hi, I'm trying to install de RSPerl module and i have some problems trying to test it. I've tried to contact with the author but the e-mail address seems not to exist. Hope that anyone in this list could explain me a little about this problem. I have a bash shell and what i do is the following: #PERLLIB=/usr/lib/R/library/RSPerl/share/blib/arch:/usr/lib/R/library/RSPerl/share/blib/lib #

Hello I will appreciate your help with the following. Running a script in R 2.14.1 under windows vista I get the following error message: Error in ifelse(append, "a", "w") : (list) object cannot be coerced to type 'logical' However, the very same script runs perfectly well under Ubuntu. My understanding is that this type of error is associated to

Hello This is a simple question but I couldn't google an answer. In the procrustes function of the vegan package, one uses plot(procrustes_object, kind=2) to obtain a plot of the residual differences. For instance: data(varespec) vare.dist <- vegdist(wisconsin(varespec)) library(MASS) mds.null <- isoMDS(vare.dist, tol=1e-7) mds.alt <- isoMDS(vare.dist,

Does anyone can provide a code to implement least median squares regression in R (not using the lqs function or calling C functions)? Reason: teaching/learning purposes Thanks PM

Hello, the R people. I look for robust regression in R. This method is available in S, its name is rreg. Colud anyone teach me ? -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the

Hi, I have been using the lqs function with method='lms'. However the results I get are a little different from the results noted by Rousseeuw & Leroy (Robust Regression and Outlier Detection) and I was wondering how to use these results for outlier detection. I'm using the stackloss dataset, for which the original Rousseeuw et al. program points out that observations 1,2,3,4

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Hello, Situation: We are in a school class every student logs on with the same account. Until now we had Shares that were accessable for everybody and it was therefore possible to look into and edit/delete other's files. Plan: Create a share that can be clicked on which then asks for User/Pass and directly maps to the User's home Directory upon auth. User auth is done through LDAP

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 severals R documentation (Fox, Ripley and

Hi, I have a linear mixed-effects model object and want to extract the 95% confidence intervals for the fixed and random effects, respectively. I found the function intervals() for confidence intervals for the fixed effects but no corresponding function for the random effects. Does it exist or do I have to calculate the confidence intervals for the random effects myself? Greetings, joerg

Hi, does anybody know of a nice test to detect trend turning points in time series? Possibly with reference? Thanks, joerg

Hi, concerning my earlier mail, maybe someone has noted from the variable names that I try to analyse mircoarrary experiments. Does anybody know of a R-implementation of the two-step mixed-model normalization procedure proposed by Wolfinger et al. (2001) J. Comput. Biol. 8:625-637? That would be great, best, joerg

Hi, I have two non-normal distributions and use interquartile ranges as a dispersion measure. Now I am looking for a test, which tests whether the interquartile ranges from the two distributions are significantly different. Any idea? Thanks, joerg [[alternative HTML version deleted]]

Has anybody written or located a robust verion of Var(X)? ______________________________________________________ Get Your Private, Free Email at http://www.hotmail.com -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in

Since this has come up already: It is a good idea to re-install all packages for a minor-version increment of R, e.g. 2.5.1 -> 2.6.0 (it is major.minor.patchlevel). This is most easily done by > update.packages(checkBuilt=TRUE, ask=FALSE) However, if you don't want to do that yet, be aware that - Certain S4-using packages must be reinstalled, and using old versions can make R

Hello, I am looking for the XML Package for Windows or any package, which would enable me to use the function "xmlTreeParse". In a thread dating from 2001, the same question is raised: >>Griffith Feeney wrote: >> >> Has anyone gotten the XML package (R News 1-1:24) with R running on Windows >> (95 or 98 or 2000)? I've looked at the omegahat, expat and libxml

Dear r-help, Is there any available description of the components of lqs objects found in the package "lqs"? > names(slts) [1] "crit" "sing" "coefficients" "bestone" [5] "fitted.values" "residuals" "scale" "terms" [9] "call"

Hello I would appreciate your help on the followig. I want to generate random binary matrices but I need to discard those with all-1 rows. That is, for a 10x10 matrix with five 1's [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 0 0 0 0 0 0 0 0 0 1 [2,] 0 0 0 0 0 0 1 0 0 0 [3,] 0 0 0 0 0 0 1