similar to: plot as .ps file: where are the axes and labels gone

am I right in the assumption, that for calculation of the condition numbers I have to use the correlation matrix of X, and not t(x) %*% x? > e <- eigen(t(x) %*% x) better (x must not have a first column of ones): > e <- eigen(cor(x)) > e$val [1] 6.6653e+07 2.0907e+05 1.0536e+05 1.8040e+04 2.4557e+01 2.0151e+00 > sqrt(e$val[1]/e$val) [1] 1.000 17.855 25.153 60.785 1647.478

I am just about working through Faraways excellent tutorial "practical regression and ANOVA using R" on page 24 he makes the x matrix: x <- cbind(1,gala[,-c(1,2)]) how can I understand this gala[,-c(1,2)])... I couldn't find an explanation of such "c-like" abbreviations anywhere. thanks for a hint. another problem: I couldn't load the faraway library, using the

Dear R-users, dear Prof. Ripley as package maintainer I tried to investigate the odd error, when I call nnet together with a 'weights' parameter, using the 'fgl' example in V&R p 348 The error I get is: Error in eval(expr, envir, enclos) : Object "w" not found I think it is a kind of scoping problem, but I really cannot see, what the problem exactly is. and

Dear R-users I use nnet for a classification (2 classes) problem. I use the code CVnn1, CVnn2 as described in V&R. The thing I changed to the code is: I define the (class) weight for each observation in each cv 'bag' and give the vector of weights as parameter of nnet(..weights = weight.vector...) Unfortunately I get an error during some (but not all!) inner-fold cv runs:

Christoph -- There was just a thread on this earlier this week. You can search in the archives for the title: "refitting lm() with same x, different y". (Actually, it doesn't turn up in the R site search yet, at least for me. But if you just go to the archive of recent messages, available through CRAN, you can search on refitting and find it. The original post was from William

Hi I need to overlay two pixmaps (library (pixmap)). One, a pixmapGrey, is the basis, and on this I need to overlay a pixmapIndexed, BUT: the pixmapIndexed has set only some of its "pixels" to an indexed color, many of its pixels should not cover the basis pixmapGrey pixel, means, for this "in pixmapIndexed not defined pixels" it should be transparent. What would you

whenever i try to run warcraft 3 via wine it comes up with a large amount of error messages but still runs... any idea on how to fix these messages? i am running it forcing opengl > > err:ole:CoCreateInstance apartment not initialised > fixme:advapi:SetSecurityInfo stub > fixme:win:EnumDisplayDevicesW ((null),0,0x33f3b8,0x00000000), stub! > fixme:win:EnumDisplayDevicesW

Hi there, I hope I can get advice regarding the calculation of leverage values or studentized residual values of a non-linear regression model. It seems like rstudent() does not work on a nls object. Many thanks in advance! Best regards, Xingli

I am working on a function that will remove outliers for regression analysis. I am stating that a data point is an outlier if its studentized residual is above or below 3 and -3, respectively. The code below is what i have thus far for the function x = c(1:20) y = c(1,3,4,2,5,6,18,8,10,8,11,13,14,14,15,85,17,19,19,20) data1 = data.frame(x,y) rm.outliers =

Hi, I wonder if anybody could help me in converting this easy SAS program into R. (I'm still trying to do that!) PROC IMPORT OUT= WORK.CHLA_italian DATAFILE= "C:\Documents and Settings\carleal\My Documents\REBECCA\stat\sas\All&nutrients.xls" DBMS=EXCEL2000 REPLACE; GETNAMES=YES; RUN; data chla_italian; set chla_italian;

Hi, I must be doing something silly here, because I can't get the studentised and standardised residuals from r output of a linear model to agree with what I think they should be from equation form. Thanks in advance, Jennifer x = seq(1,10) y = x + rnorm(10) mod = lm(y~x) rstandard(mod) residuals(mod)/(summary(mod)$sigma) rstudent(mod)

Hi all, I'm trying to apply loess regression to my data and then use the fitted model to get the *standardized/studentized residuals. I understood that for linear regression (lm) there are functions to do that:* * * fit1 = lm(y~x) stdres.fit1 = rstandard(fit1) studres.fit1 = rstudent(fit1) I was wondering if there is an equally simple way to get the standardized/studentized residuals for a

Hi, dear R pros I try to understand eigen(). I have seen, that eigen() gives the eigenvectors normalized to unit length. What shall I do to get the eigenvectors not normalized to unit length? E.g. take the example: A [,1] [,2] V1 0.7714286 -0.2571429 V2 -0.4224490 0.1408163 Calculating eigen(A) "by hand" gives the eigenvectors (example from Backhaus,

I am using the Unix version of R (version 1.7.0), installed via fink on a G4 Macintosh. I recently upgraded from version 1.6.0 and found that the "car" library now has a problem: ---Begin transcript--- >library(car) Attaching package 'car': The following object(s) are masked from package:base : dfbeta dfbeta.lm dfbetas dfbetas.lm hatvalues hatvalues.lm

Dear community, I'm having this silly problem. I've a linear model. After fixing it, I wanted to know which data had studentized residuals larger than 3, so i tried this: d1 <- cooks.distance(lmmodel) r <- sqrt(abs(rstandard(lmmodel))) rstu <- abs(rstudent(lmmodel)) a <- cbind( mydata, d1, r,rstu) alargerthan3 <- a[rstu >3, ] And suddenly a[rstu >3, ] has

Two post-doctoral positions are available from the Brain Physiology Laboratory in Paris (France). The first position is available immediately to work on spike sorting and spike train analysis. It consists in both data analysis and methods development. Familiarity with neurophysiology is not required. Familiarity with R and with some of the methodologies used: clustering, classification,

I hope this question is adequate for this list I use the nnet code from V&R p. 348: The very nice and general function CVnn2() to choose the number of hidden units and the amount of weight decay by an inner cross-validation- with a slight modification to use it for classification (see below). My data has 2 classes with unequal size: 45 observations for classI and 116 obs. for classII With

Hi, I'm running Redhat Enterprise WS 4. with kernel 2.6.9-11. Also I have the following: [root@itbsjb1 samba]# rpm -qa |grep samba system-config-samba-1.2.21-1 samba-common-3.0.10-1.4E samba-swat-3.0.10-1.4E samba-3.0.10-1.4E samba-client-3.0.10-1.4E smb.conf: [root@itbsjb1 samba]# cat smb.conf # Samba config file created using SWAT # from 127.0.0.1 (127.0.0.1) # Date:

Hi, I am trying to figure out how to get the correlation coefficient for a QQ plot (residual plot). So to be more precise, I am creating the plot like this: qq.plot(rstudent(regrname), main = rformula, col=1) But want to also access (or compute) the correlation coefficient for that plot. Thanks, Tom [[alternative HTML version deleted]]

I had a look at some influence measures, and it seems to me that currently several methods handle multiple lm (mlm) objects wrongly in R. In some cases there are separate "mlm" methods, but usually "mlm" objects are handled by the same methods as univariate "lm" methods, and in some cases this fails. There are two general patterns of problems in influence measures: