similar to: problems using 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 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"

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:

I'm trying to use least trimmed squares using ltsreg with nsamp="exact". When I use the following: rg <- ltsreg(x,y,nsamp="exact") I get: Error in lqs.default(x, y, nsamp = "exact", method = "lts") : NAs in foreign function call (arg 10) In addition: Warning message: NAs introduced by coercion Incidentally, there are no missings in x or y,

I am new to R and Im some trouble with the following question... Generate 100 standard normal N(0,1) samples of size 100, X1(k),...,X100(k) where k=1,...,100 (The k is and indicie in brackets) Calculate the sample mean for each sample. For each sample mean Xbark the 0.95-confidence interval for the mean mew=0 is given by... Ik= ( Xbark plus or minus 1.96/10) Find the number of intervals such

Hi, I want to calculate the R-squared between two variables. Can you advice me how to identify and remove the outliers before performing R-squared calculation? Thanks, Kan --------------------------------- SBC Yahoo! DSL - Now only $29.95 per month! [[alternate HTML version deleted]]

I have found that specifying different "sizes" in the sample command has a funny effect on the random sampling. The code below is a condensed version of a function I wrote to simulate a bootstrap method. For simplicity, I eliminated the internal bootstrap loop, but kept a statement to draw one bootstrap sample, because this is where the problem occurs. The output (mean(y)^2) should be

Hello, I've a problem with a self written routine taking a lot of memory (>1.2Gb). Maybe you can suggest some enhancements, I'm pretty sure that my implementation is not optimal ... I'm creating many linear models and store coefficients, anova p-values ... all I need in different lists which are then finally returned in a list (list of lists). The input is a matrix with 84 rows

Hi, I have a complex-valued vector X in C^n. Given another complex-valued vector Y in C^n, I want to find a permutation of Y, say, Y*, that minimizes ||X - Y*||, the distance between X and Y*. Note that this problem can be trivially solved for "Real" vectors, since real numbers possess the ordering property. Complex numbers, however, do not possess this property. Hence 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

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

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, but when I used this package the only results returned were equivalent to

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

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, 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

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

Hi, I'm completely new to R, I am all at sea with the interface and the confusing help files, so would appreciate some help to do a simple task. Need to present the mean and variance of 100 different samples of poisson distributions (N=1000, with fixed lambda) in a file in two columnns, and then produce histograms. So far I have figured out: > N <- 1000 > x <- rpois(N, 3.1) ,

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]: