similar to: robustbase: cannot install

Subject: Re: [R-sig-Debian] ubuntu problem with 'r-cran-robustbase' [FWD Agustin Lobo] Date: Tue, 12 May 2009 13:30:49 +0200 From: Agustin Lobo <aloboaleu at gmail.com> Reply-To: aloboaleu at gmail.com To: Dirk Eddelbuettel <edd at debian.org> CC: Martin Maechler <maechler at stat.math.ethz.ch>, R-SIG-Debian at stat.math.ethz.ch References: <18953.17704.527898.355877

Dear list, I'm forwarding these 2 messages as suggested by the package developer. My system is > sessionInfo() R version 2.9.0 (2009-04-17) i486-pc-linux-gnu on Ubuntu 8.04, with r-base-core, r-base-dev and r-recommended installed from binaries through Synaptic. I normally install the rest of packages using install.packages() from within R (started from an xterminal by su) Agus

Agustin, posted on R-help. I think the problem is one of the debian/ubuntu package 'r-cran-robustbase' and its setup or (missing?) dependencies. I can confirm Agustin's problem, working on Ubuntu 8.04.2 (8.04 is a "LTS" = long time support version). apt-get install r-cran-robustbase works fine, but when trying to load the package, there's a DLL - dependency on

Dear All, in the sources of robustbase, there appears a function called rPsort() (say l253 of qn_sn.c). I could not find its source in the robustbase package and a google search yields too many unrelated response. Can anyone point to its source ? thanks, -- View this message in context: http://r.789695.n4.nabble.com/Robustbase-source-question-tp3459966p3459966.html Sent from the R help

Hey there. I am running a multiple regression and want to see whether a robust regression would provide different results, since there is some heteroscedasticity and other minor violations of regression assumptions. When I run the model using the robustbase package, > modelrob=lmrob(m1) I receive the following error: > Error in qr.default(x * sqrt(ret$weights)) : > NA/NaN/Inf in

Martin, Although I did remove the ln libRlapack.so -> ./lapack.so and sudo apt-get install r-cran-robustbase went fine (as does if the installation is done through Synaptic), once I start R I get: > require(robustbase) Loading required package: robustbase Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared library

Hi, I encountered a segfault, memory not mapped error when using adjbox in robustbase. In trying to recreate the issue I found that the error occurs only for large sample size. Here is the code. > require(robustbase) Loading required package: robustbase > x <- rnorm(10) > y <- rep(1, 10) > adjbox(x ~ y) ## gives a plot > x <- rnorm(10000) > y <- rep(1,

With a recent SVN build (R Under development (unstable) (2013-07-10 r63264) -- "Unsuffered Consequences"), I'm having trouble installing the robustbase package. The bottom line is that I *think* it's a 32-bit-system problem, but I could easily be mistaken. robustbase is passing its package checks: http://cran.r-project.org/web/checks/check_results_robustbase.html ... but from

This is my first post requesting help to this mailing list. I am new to R. My apologies for any breach in posting etiquette. I am new to this language and just learning my way around. I am attempting to run some sample code and and am confused by the error message: Loading required package: rrcov Error in fitNorm2(fdat[, "FSC-H"], fdat[, "SSC-H"], scalefac = ScaleFactor) :

hello list, i'm a bit puzzled by the error message i get when i copy past this in R:

Dear R Users, Is there a known problem with downloading packages robustbase and tseries from the UK CRAN website ? Thanks in advance, Tolga ========================================================= R version 2.7.1 (2008-06-23) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to

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

Hi all, I have been trying to add the line: h = n - p0 + 1; just after h = n / 2 + 1; (line 131) in the source code (the original paper mention this is possible for p0&lt;n). with p0 declared as an int (actually i used the same declaration protocol as n everywhere in the code). The &quot;new&quot; source compiles, but when i give it reasonable values of p0, it runs unto

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

Hello. I've got a dataset that may have outliers in both x and y. While I am not at all familiar with robust regression, it looked like the function lmrob in package robustbase should handle this situation. When I try to use it, I get: Too many singular resamples Aborting fast_s_w_mem() Looking into it further, it appears that for an indicator variable in one of my interaction terms, 98%

Hi all and thanks for your time in advance, I can't figure out why summary.lmrob complains when lmrob is used on a zooreg object. If the zooreg object is converted to vector before calling lmrob, no problems appear. Let me clarify this with an example: >library(robustbase) >library(zoo) >dad<-c(801.4625,527.2062,545.2250,608.2313,633.8875,575.9500,797.0500,706.4188,

I am looking at MM-estimates for some interlab comparison work. The usual situation in this particular context is a modest number of results from very expensive methods with abnormally well-characterised performance, so for once we have good "variance" estimates (which can differ substantially for good reason) from most labs. But there remains room for human error or unexpected chemistry

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

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)

Dear R-experts, I guess I have a problem with my fast function (fast tau estimator) here below. Indeed, zero errors look highly suspicious. I guess there is a bug in my R code. How could I correct my R code ? # install.packages( "robustbase" ) # install.packages( "MASS" ) # install.packages( "quantreg" ) # install.packages( "RobPer" ) #