similar to: documentation and plotting with lqs

Is there a way of getting a list of indices or something indicating which set of points lqs when doing a regression? The $bestone, seems to return only 2 pts. no matter how good or bad the fit. I checked the archive for the past few months, but didn't find anything. thanks in advance, Mark Hall -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help

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 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

Dear List-Members, I have a problem with the function lqs() from package MASS. In some cases it produces different results for the same settings and needs a random seed to be set, in other cases not. I really cannot understand, why this happens. As well I do not understand what exactly you need the random seed for. Is it a starting point for iterations? Or do different results occur because of

I now have versions of code that is destined (I believe) for 0.63 which is in a suitable state for comment. The files are at ftp://ftp.stats.ox.ac.uk/pub/R (Our www server is being moved, so may be intermittently down, but this ftp server should be stable.) All are R packages, for the moment for personal use only (no re-distribution). Use with 0.62.3 or 0.63 (although I am aware of some

Here is an example given from ?yags library(methods) data(stackloss) Y1 <- yags(stack.loss~Air.Flow,id=1:21, data=stackloss) How can I access parts of the output. I tried: > str(Y1) Formal class 'yagsResult' [package "yags"] with 25 slots ..@ coefficients : num [1:2] -44.13 1.02 ..@ coefnames : chr(0) > Y1$coefnames Error in Y1$coefnames : $

I tried building R-1.6.1 under Mac OS X 10.2.2 and experienced the following build failure: <...stuff omitted...> cc1: warning: changing search order for system directory "/usr/local/include" cc1: warning: as it has already been specified as a non-system directory gcc -bundle -flat_namespace -undefined suppress -L/usr/local/lib -o ctest.so ansari.o chisqsim.o d2x2xk.o

Dear Keith, >>>>> <Keith.Jewell at campdenbri.co.uk> >>>>> on Thu, 16 Jul 2015 08:58:11 +0000 writes: > Dear R Core Team, > Last week I made a post to the R-help mailing list > ?predict.poly for multivariate data? > <https://stat.ethz.ch/pipermail/r-help/2015-July/430311.html> > but it has had no responses so I?m

Dear r-devel members, I tried to build R packages on a PC running Windows XP but experience problems. However, it is ok when there is no inst directory in a package. Any help would be appreciated. The following is an example, C:\work>R CMD check VR_7.2-19.tar.gz * checking for working latex ... OK * using log directory 'C:/work/VR.Rcheck' * using R version 2.1.1, 2005-06-20 *

Dear list, (this is a follow up from a previous query) Why does R CMD INSTALL write most of its messages to stderr? If it wrote to stdout, then we could capture its output within an R session when calling sink("stdout.txt", type="output") install.packages("MASS", type="source") sink() As it stands, the stderr messages can't be captured via

Dear list member, by running Rcmd check on a package where a customised 'CITATION' file should be included instead of the automatically produced one, the following error occurs: adding build stamp to DESCRIPTION installing NAMESPACE file and metadata installing R files installing inst files FIND: Parameter format not correct make[2]: *** [c:/R/packages/urca/inst] Error 2 make[1]:

can you recommend a good manual for R that starts with a data set and gives demonstrations on what can be done using R? I downloadedR Langauage definition and An introduction to R but haven't found them overly useful. I'd really like to be able to follow some tutorials using a dataset or many datasets. The datasets I have available on R are Data sets in package 'datasets':

Hi, trying to do a robudt regression of a two-way linear model, I keep getting the following error: > lqs(obs ~ y + s -1,method="lms", contrasts=list(s=("contr.sum"))) Error: lqs failed: all the samples were singular Robust regression with M-estimators works (also regular least square fits, of course): rlm.formula(formula = obs ~ y + s - 1, method = "M",

Hi, I installed Ubuntu 13.10 on Android 4.4.2 (Nexus 5). I also installed all the tools I have on my Desktop Ubuntu without problems on the Nexus 5 Ubuntu. I then wanted to install R-3.0.2 (from source). 'make' runs fine up to installing MASS: make[2]: Entering directory `/usr/local/R/R-3.0.2-build/src/library/Recommended' begin installing recommended package MASS During startup -

As shown below, the build process fails with only vague messages, leaving me clueless as to how to resolve. Thanks, in advance, for any help that you may offer. Mike -------------------------------------- # ./configure --prefix=/SOURCES/R-2.5.1 --with-iconv=no ... ... ... R is now configured for sparc-sun-solaris2.8 Source directory: . Installation directory: /SOURCES/R-2.5.1 C compiler: gcc

I am having trouble compiling R-2.6.2 on suse linux x86_64 using the intel compiler. I read section C.2.1 Intel compilers in the R Installation and Administration manual, and put CC=icc CFLAGS="-g -O3 -wd188 -ip" F77=ifort FFLAGS="-g -O3" ICC_LIBS=/opt/intel/cce/10.1.012/lib IFC_LIBS=/opt/intel/fce/10.1.012/lib/ LDFLAGS="-L$ICC_LIBS -L$IFC_LIBS -L/usr/lib64"

Hi all, With the bug in tre identified I am trying to move forward - one step at a time. As I am getting some errors that prevent make completing with version 3.2.3, and R-devel introduces new issues (that I will face when I get to them) I would appreciate some guidance with output of "make check" (of 3.1.3) and the final message I run into when trying to build 3.2.3. Maybe they

> 3x4 Error: unexpected symbol in "3x4" R has no idea that you equate "x" as multiplication.. use an astrix > 3*4 [1] 12 dominic wrote > > This is basically my code: > > library(MASS) > lmsreg(formula = b0 ~ b1 + b3 + b1xb2, data=mydata) > > b1xb2 is an interaction but it was the centered value for a continuous > variable times a

Hello Can anyone tell me what I am doing wrong below? My Y and y_hat are the same. A<-scale(stackloss) n1<- dim(A)[1];n2<-dim(A)[2] X<-svd(A) Y<- matrix(A[,"stack.loss"],nrow=n1) Y y_hat <-matrix((X$u%*% t(X$u))%*%Y,nrow=n1,byrow=T) y_hat [[alternative HTML version deleted]]

R Listers, One of the list contributors suggested I abandon attempts to build R-1.9.1 and focus on building R-2.3.1. I believe the main set of packages have been built properly (with some changes to the code) - however, when building the Recommended packages, the build fails. CODE CHANGES: ============= 1. My C compiler requires a ";" on line 589 of ..../src/main/printutils.c. Here