similar to: error in qr(x)

Hello, I computed acf() and have an array as output. now I would like to have only one matrix or data frame (not yet familiar with the nomenclature) extracted from this array. or even only the first row of each matrix. the first part of my data "test" is called $acf ,1 , , 1 , , 2 1, , ... ... 2, , .. ... I tried several names but nothing wants to work, I only

hello I read "Practical Time Series" (Gareth Janacek; 2001) and they presented e.g the smoothing functions msmooth(x,k) or the bivariate function crosscorr(x,y,k), but both didn't work on my machine. I only load the ts library, is another library necessary or did this function change since 2001? Is there a more recent and detailed manual for ts? thanks, cheers Martin -- Martin

Hello, I have two dataframes, one with a time series of variables and another one with biological data of each plot. the column names correspond to each other plot1 plot 2....... 1983 ... .... 1984 ... .... ... and plot 1 plot2 1 ... ... 2 is it somehow possible to use acf() with two data frames and get a p values for the whole correaltion of these

Hello R user, I downloaded grasper_0.3-2.tar.gz and installed it as described. $ su $ R CMD INSTALL grasper_0.3-2.tar.gz $ R that seems to work, but > grasp.GUI() doesn't work. I read the note, that graspeR need mgcv (downloaded), MASS, modreg and tcktk . I haven't found the last 3 packetages in the Suse 8.1 contrib list. Where can I find them? Or what could be the problem? thanks in

Hi, I built and installed R-base-1.7.0 on SuSE 8.2 without any problems, but the interactive R interpreter, has problems with cursor movement: > ls() character(0) > ^[[A^[[B^[[D^[[C^[[A^[[D^[[C^[[B^[[D^[[A These ugly characters are produced by the arrow keys. Does anyone know how to fix that problem? Ciao Sebastian

Hi, I have a dataset of dimensions 50 x 15000, and tried to use princomp or prcomp on this dataset with 15000 columns as variables, but it seems that the 2 functions can;t handle this large number of columns, anyone has nay suggestions to get around this? Thanks --------------------------------- [[alternate HTML version deleted]]

Hy there, I have a problem with Samba 2.2.5 (on AIX 4.3) concerning a printer share. I set up a few printer share which work well. Now I want to restrict the access to one of them. In order to achieve this I put in a hosts deny=all hosts allow=<IP-Adresses of hosts, which should be allowed to print> in the corresponding printer-share-section. What happens is this: non

Dear R-devel, There seems to be a discrepancy in the order in which lm and rlm evaluate their arguments. This causes rlm to sometimes produce an error where lm is just fine. Here is a little script that illustrate the issue: > library(MASS) > ## create data > n <- 100 > dat <- data.frame(x=rep(c(-1,0,1), n), y=rnorm(3*n)) > > ## call lm, works fine > summary(lm(y ~

Dear Group, I am having trouble with using rlm on multivariate data sets. When I call rlm I get Error in lm.wfit(x, y, w, method = "qr") : incompatible dimensions lm on the same data sets seem to work well (see code example). Am I doing something wrong? I have already browsed through the forums and google but could not find any related discussions. I use Windows XP and R

Hi, I am trying to build a series of rlm models. I have my data frame and the models will be built using various coulmns of the data frame. Thus a series of models would be m1 <- rlm(V1 ~ V2 + V3 + V4, data) m2 <- rlm(V1 ~ V2 + V5 + V7, data) m3 <- rlm(V1 ~ V2 + V8 + V9, data) I would like to automate this. Is it possible to use a string in place of the formula? I tried doing: fmla

Hello, I have a simple xyplot with rlm lines. I would like to add the a and b coefficients (y=ax+b) of the rlm calculation in each panel. I know I can do it 'outside' the xyplot command but I would like to do all at the same time. I found some posts with the same question, but no answer. Is it impossible ? Thanks in advance for your help. Ptit Bleu. x11(15,12) xyplot(df1$col2 ~

I keep coming back to this problem of singular fits in rlm (MASS library), but cannot figure out a good solution. I am fitting a linear model with a factor variable, like lm( Y ~ factorVar) and this works fine. lm knows to construct the contrast matrix the way I would expect, which puts the first factor as the baseline level. But when I try rlm( Y ~ factorVar) I get the message "'x'

Dear List, I used rlm to calculate two regression models for two data sets (rlm due to two outlying values in one of the data sets). Now I want to compare the two regression slopes. I came across some R-code of Spencer Graves in reply to a similar problem: http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg06666.html The code was: > df1 <- data.frame(x=1:10, y=1:10+rnorm(10))

Hi all, I am reading the MASS book but it doesn't give examples about the diagnosis and model checking for rlm... My data is highly non-Gaussian so I am using rlm instead of lm. My questions are: 0. Are goodness-of-fit and model-checking using rlm completely the same as usual regression? 1. Please give me some pointers about how to do goodness-of-fit and residual diagnosis for

Hello all, I'm using R2.7.0 (on Windows 2000) and I'm trying do run a robust regression on following model structure: model = "Y ~ x1*x2 / (x3 + x4 + x5 +x6)" where x1 and x2 are both factors (either 1 or 0) and x3.....x6 are numeric. The error code I get when running rlm(as.formula(model), data=daymean) is: error in rlm.default(x, y, weights, method = method, wt.method =

Hello, I'm trying to do a little rlm of some data that looks like this: UNIT COHORT perdo adjodds 1010 96 0.39890 1.06894 1010 97 0.48113 1.57500 1010 98 0.36328 1.21498 1010 99 0.44391 1.38608 It works fine like this: rlm(perdo ~ COHORT, psi=psisquare) But the problem is that I have about 100 UNITs, and I want to do a

This message also reports wrong estimates produced by lmRob.fit.compute() for nested factors when using the correct contrast matrix. And in these respects, I have found that S-Plus behaves the same way as R. Using the three available contrast types (sum, treatment, helmert) with lm() or lm.fit(), but just contr.sum with rlm() and lmRob(), and small examples, I generated contrast matrices for

Hi, I would appreciate of someone could explain how the residual standard error is computed for rlm models (MASS package). Usually, one would expect to get the residual standard error by > sqrt(sum((y-fitted(fm))^2)/(n-2)) where y is the response, fm a linear model with an intercept and slope for x and n the number of observations. This does not seem to work for rlm models and I am wondering

Dear all, When calling rlm with the following data, I get an error. (R v.1.8.1, WinXP Pro 2002 with service pack 1.) > d <- na.omit(data.frame(CPRATIO, HEIGHTZ, FAMILYID)) > c <- tapply(d$CPRATIO, d$FAMILYID, mean) > h <- tapply(d$HEIGHTZ, d$FAMILYID, mean) > c 1 2 3 6 7 9 10 11 6.000000 2.500000 3.250000

Dear r-bugs, I looked over the FAQ. Hope I'm reporting this correctly. I ran this on both solaris and windows. I've provided terminal snapshots which include how R was called from the command line, and the result of version at the R prompt. I have attached the .r file, and the data file and the output snapshots. Below also find everything except only a few lines of the data file. Note