similar to: msoffice: which version (97, 2k, xp) do you recommend

Dear R-users How can I get the eigenvalues out of an lda analysis? thanks a lot christoph -- Christoph Lehmann <christoph.lehmann at gmx.ch>

Hi Since the 'equal slope' assumption doesn't hold in my data I cannot use a proportional odds model ('Design' library, together with 'Hmisc'). I would like to try therefore a partial proportional odds model Please, could anybody tell me, where to find the code and how to specify such a model ..or any potential alternatives many thanks for your kind help christoph

Dear R experts I have the follwoing data V1 V2 1 -5.8000000 0 2 -4.8000000 0 3 -2.8666667 0 4 -0.8666667 0 5 -0.7333333 0 6 -1.6666667 0 7 -0.1333333 1 8 1.2000000 1 9 1.3333333 1 and I want to know, whether V1 can predict V2: of course it can, since there is a perfect separation between cases 1..6 and 7..9 How can I test, whether this conclusion (being able to assign an

Hi (1)In polr(), is there any way to calculate a pseudo analogue to the R^2. Just for use as a purely descriptive statistic of the goodness of fit? (2) And: what are the assumptions which must be fulfilled, so that the results of polr() (t-values, etc.) are valid? How can I test these prerequisites most easily: I have a three-level (ordered factor) response and four metric variables. many

Hi I need to define the following c("one group" = class.weight[2], "other group" = class.weight[1]) #class.weight = c(1,2) but I don't like the hard-coded way and would like to use my.group <- array(c("one group", "other group")) but now c(my.group[1] = class.weight[2], my.group[2] = class.weight[1]) gives an error how can I solve this

Hi what would you recommend to compare classification methods such as LDA, classification trees (rpart), bagging, SVM, etc: 10-fold cv (as in Ripley p. 346f) or leaving-one-out (as e.g. implemented in LDA)? my data-set is not that huge (roughly 200 entries) many thanks for a hint Christoph -- Christoph Lehmann <christoph.lehmann at gmx.ch>

Hi I have a huge array with series of data. For each cell in the array I fit a linear model, either using lm() or gls() with lm() there is no problem, but with gls() I get an error: Error in glsEstimate(glsSt, control = glsEstControl) : computed gls fit is singular, rank 2 as soon as there are data like this: > y1 <- c(0,0,0,0) > x1 <- c(0,1,1.3,0) > gls(y1~x1)

Hi It seems, I just miss something. I defined treshold <- function(pred) { if (pred < 0.5) pred <- 0 else pred <- 1 return(pred) } and want to use apply it on a vector sapply(mylist[,,3],threshold) but I get: Error in match.fun(FUN) : Object "threshold" not found thanks for help cheers chris -- Christoph Lehmann <christoph.lehmann at gmx.ch>

Dear R users I have a two-dimensional array, whose values I want to plot, using the pixmapGrey class. Plotting works fine, and now I would like to be able to identify some of the points in the plot using identify(). But I get the following message while pressing the left mouse button: > plot(pixmapGrey(fmri.vtc[,,slice,volume])) > identify(fmri.vtc[,,slice,volume]) warning: no point with

Hello, I am trying to use the cdrom from one Sun server for software installation on NT Clients. I am using samba 1.9.18p7 on solaris 2.5.1 Here is my smb.conf: [global] workgroup = WIWI server string = Windows NT Server 5.0 debug level = 2 log file = /opt/samba/var/log.%m max log size = 10 socket options = TCP_NODELAY IPTOS_LOWDELAY read prediction = yes interfaces =

Hi Since a stepwise procedure for variable selection (as e.g. in SPSS) for a LDA is not implemented in R and anyway I cannot be sure, that all the required assumptions for e.g. a procedure using a statistic based on wilks' lambda, hold (such as normality and variance homogeneity) I would like to ask you, what you would recommend me: shall I e.g. define a criterion such as the error-rate

again, under another subject: sorry, maybe an all too trivial question. But we have power data from J frequency spectra and to have the same range for the data of all our subjects, we just transformed them into % values, pseudo-code: power[i,j]=power[i,j]/sum(power[i,1:J]) of course, now we have a perfect linear relationship in our x design-matrix, since all power-values for each subject sum up

Hi In R 1.7 the following worked fine: > array(list(),c(2,5)) [,1] [,2] [,3] [,4] [,5] [1,] NULL NULL NULL NULL NULL [2,] NULL NULL NULL NULL NULL now in R 1.8.1 I get the error: Error in rep.int(data, t1) : invalid number of copies in "rep" In addition: Warning message: NAs introduced by coercion thanks for help, I need this possibility for storing objects (lm results) in

Hi my installation of ggobi (!) was successful, but when I try to install Rggobi as described on http://www.ggobi.org/INSTALL.html: as non-su: R_HOME=/usr/lib/R export R_HOME GGOBI_ROOT=/usr/local/src/ggobi export GGOBI_ROOT R_LIBS=/usr/lib/R/library export R_LIBS as: su ln -s $GGOBI_ROOT/lib/libggobi.so /usr/lib/. ln -s $GGOBI_ROOT/lib/libgtkext.so /usr/lib/. R CMD INSTALL Rggobi_0.53-0.tar.gz

Hi I didn't find this in the manual: I need to change the width of a plot while I use sweave, so which command/parameters should I insert below, to change the width of a plot \begin{figure}[htbp] \begin{center} <<echo=TRUE, fig=TRUE>>= plot(Re(q),ylab ="",type="o",col="blue",lwd=1, sub=mystring) @ \caption{Original stick function (stimulus

Hi I have calculated lots (>1000) of linear models and would like to store each single result as an element of a 3D matrix or a similar storage: something like glm[i][j][k] = lm(...) Since I read that results are lists: Is it possible to define a matrix of type list? Or what do you recommend? Many thanks Christoph -- Christoph Lehmann <christoph.lehmann at gmx.ch>

Dear R and sweave users A further problem, which I couldn't resolve, using the manual: In R I use the split.screen command to put e.g. two timecourses one above the other into one plot: split.screen(c(2,1)) screen(1) plot(stick,type='h', col="red",lwd=2) screen(2) plot(deconvolution.amplitude,type='h',col="blue",lwd=2) Is there a similar way, doing this

Hi I used princomp on a dataset x[!sub,]. How can I get the scores for another dataset, say x[sub,]? I didn't succeed using predict() thanks for a hint cheers christoph -- Christoph Lehmann <christoph.lehmann at gmx.ch>

Hi I use sweave for excellent pdf output (thank you- Friedrich Leisch). I have just one problem. Quite often it happens, that the graphics are not at the place where I expect them, but (often on a separate page) later on in the pdf. How can I fix this, means how can I define, that I want a graphic exactly here and now in the document? Many thanks and best regards Christoph -- Christoph

Hi I have a data.frame with a grouping variable having the levels C, mild AD, mod AD, O and S since I want to compute a lda only for the two groups 'C' and 'mod AD' I call lda with data=subset(mydata.pca,GROUP == 'mod AD' | GROUP == 'C') my.lda <- lda(GROUP ~ Comp.1 + Comp.2 + Comp.3 + Comp.4+ Comp.5 + Comp.6 + Comp.7 + Comp.8 ,