similar to: a question about LMS and what constitutes outliers

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:

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",

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"

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,

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

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

Readers, Using version 251 I tried the following command: lm(y~a+b,data=datafile) Resulting in, inter alia: ... coefficients (intercept) a 1.2 3.4 Packages installed: acepack ace() and avas() for selecting regression transformations adlift An adaptive lifting scheme algorithm akima Interpolation of irregularly spaced

I just successfully compiled R-1.6.0 on a Red Hat 7.2 machine. When I tried to install "grid" from source, I got this error. Any suggestions? I don't think it is a dependency problem. I also attach the output from library(). Yuelin Li. ------------- > install.packages("grid") trying URL `http://cran.r-project.org/src/contrib/PACKAGES' Content type

Hello, I'm trying to create birth centile charts from about 90000 birth weights using the package lmsqreg. As this is not a CRAN package I have problems finding any examples, which explain how to estimate the LMS parameters needed for the equivalent degrees of freedom. (I only have some basic understanding of statistics, I roughly understand the formulas, but then I don't know how to

Everything is ok on Firefox, IE, and iPad. Thanks, Erin On Tue, Jan 8, 2013 at 7:58 PM, Erin Hodgess <erinm.hodgess at gmail.com> wrote: > Dear R People: > > Has anyone used R2HTML in web files that were on the Blackboard LMS, please? > > I'm starting to do these but wanted to know if there were any > potential pitfalls. > > Thanks, > Erin > > > --

Dear R People: Has anyone used R2HTML in web files that were on the Blackboard LMS, please? I'm starting to do these but wanted to know if there were any potential pitfalls. Thanks, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at gmail.com

Right. The methods such as as.data.frame.numeric don't get dispatched, basically because RSMethods tries to interpret class(x) in the S4 sense (so, e.g. a numeric vector has class "numeric"). Problems can then come from different semantics for S3-style and S4-style methods. The older methods don't dispatch on the mode of vectors (or equivalently, on the value of

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

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 : $

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

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 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 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

Hello R-users, Is there any more sophisticated way how to identify the dataset outliers other then seeing them in boxplot? I wanna exclude them from further analysis and I am interested in their position in my vector data. Rado -- Radoslav Bonk M.S. Dept. of Physical Geography and Geoecology Faculty of Sciences, Comenius University Mlynska Dolina 842 15, Bratislava, SLOVAKIA tel: +421 2 602