similar to: sweave: graphics not at the expected location in the pdf

Hi, I'm creating a lot of tables in a file for inclusion in a Latex document. When I try to compile that document there is an error "too many unprocessed floats." Is there a way to correct this? Also, in a Latex table I want R to put in a $\beta$ in the caption, but it puts a weird system character instead of the \b Brian

Is it possible to write the output/results (redirect) to a latex file? Jeff. Jeff D. Hamann Hamann, Donald & Associates, Inc. PO Box 1421 Corvallis, Oregon USA 97339-1421 Bus. 541-753-7333 Cell. 541-740-5988 jeff_hamann at hamanndonald.com www.hamanndonald.com -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

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

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

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 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

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

Hello list, i've got some problems getting a E1 line with a E100P up and running (germany). # cat /proc/zaptel/1 Span 1: WCT1/0 "Digium Wildcard E100P E1/PRA Card 0" HDB3/CCS/CRC4 YELLOW RED "YELLOW RED" sounds not so good. When launching asterisk, enabling pri debug on that span, i see outgoing attempts: ;---------- snip -------- > [00 01 7f ] > Unnumbered

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

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

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>

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

Does anyone know of an implementation in R of the Hodges-Lehmann nonparametric difference between two groups? I am interested in the estimate of the difference and the CI or significance of that difference. I did some quick searching and didn't see it, but I may not have been looking for the right name, etc. Thanks, Sean

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, in Latex I get the table using: \begin{table}[H] \centering \renewcommand{\arraystretch}{1.3} \setlength{\tabcolsep}{18pt} \begin{tabular}{cc} \hline Idade & Frequ?ncia \\ \hline $18 \vdash 26$ & 11 \\ $26 \vdash 34$ & 8 \\ $34 \vdash 42$ & 26 \\ $42 \vdash 50$ & 20 \\ $50 \vdash 58$ & 23 \\ $58 \vdash 66$ & 30 \\ $66

While using the Hodges Lehmann Mean in DescTools (DescTools::HodgesLehmann), I found that it generated incorrect answers (see <https://github.com/AndriSignorell/DescTools/issues/97> https://github.com/AndriSignorell/DescTools/issues/97). The error is driven by the existence of tied values forcing wilcox.test in Base R to switch to an approximate algorithm that returns incorrect results - see

Hi list, I was using Sweave and was wondering if anyone has had any luck changing the font colors of the code chunks. For instance, in my .Rnw preample I tried including: === \usepackage[usenames]{colors} \definecolor{darkred}{rgb}{0.545,0,0} \definecolor{midnightblue}{rgb}{0.098,0.098,0.439} \DefineVerbatimEnvironment{Sinput}{Verbatim}{fontshape=sl,formatcom={\color{midnightblue}}}

Hi I have a data.frame with say 10 continuous variables and one grouping factor (say 3 levels) how can I easily (without loops) apply for each continous variable e.g. an aov, with the grouping factor as my factor (or if the grouping factor has 2 levels, eg. a t-test) thanks for a hint cheers christoph

I have the following simple situation: tt <- data.frame(c(0.5, 1, 0.5)) names(tt) <- "a" plot(tt$a, type = 'o') gives the following plot ('I' and '.' represent the axis): I I I X I I I X X I........... 1 2 3 what do I have to change to get the following: I I I X I I I X X I..................... 1 2 3