similar to: FAQ/Website problems (PR#2840)

Hi All: I am clustering 500 genes using hclust of R. Visualizing cluster membership becomes difficult with so many genes in each cluster...Is there a way of printing the dendrogram in multiple pages so that I can clearly see what is in each cluster? Thanks in advance. Karthi.

As many of you have probably realized, the spam filtering at @stat.math.ethz.ch has been dead for since yesterday (09-25) ~16:50 till today ~08:30. The sudden death may have been caused by unrelated installation of some perl modules (spamassassin *is* running on perl) by our IT staff. We are very sorry for this event. On the bright side: You have been able to get a glimpse of what you are

Has anyone ported the Bagplot function by Rousseeuw, Ruts, and Tukey from S to R? The S function comprises a script and a FORTRAN function. I assume porting is relatively uncomplicated, but since I have not done any porting before I would not want to invest the effort if a port is readily available.

Dear R experts. 'D()' function recognizes some of the analitical functions, such as sin, cos, etc. But I'd like to take analytical derivatives from asin, atan etc. functions. Are there any R packages providing that features? Thanks. -- Timur.

We have locally collected good experience the last few weeks using procmail-spam filtering, inclduing spamassassin to the procmail filters. The last two spams that went past the majordomo filters (the "traditional ones I've been using) through to R-devel both were not delivered to me, be but caught by the filters. I have now collected a bit more of a week experience using the new scheme

Is there a way of extracting mean distance or dissimilarity for a given strata from a 'dist' or 'dissimilarity' object, e.g. extract mean distances for each species in Anderson's iris data? data(iris) iris.dist<-dist(iris[,1:4]) then what? Mikkel Grum, PhD Genetic Diversity Scientist International Plant Genetic Resources Institute (IPGRI) Sub-Saharan Africa Group ***

Full_Name: Jerome Asselin Version: 1.6.2 OS: RedHat Linux 7.2 Submission from: (NULL) (142.103.173.179) Should be an easy fix... Consider the examble below: plot(0,0) legend(0,0,c("Hello!","Hi!"),pch=1:2,lty=1:2,trace=T) It gives the following trace: > plot(0,0) > legend(0,0,c("Hello!","Hi!"),pch=1:2,lty=1:2,trace=T) xchar= 0.05178 ;

Hi, I thought it would be convenient if the check.names argument to read.table, which currently can only be TRUE/FALSE, could take a function value as well. If the function is supplied it should be used instead of the default make.names. Here is an example where it can come in handy. I tend to keep my data in coma-separated files with a header line. The header line is prefixed with a comment

Dear S-PLUS/R users: Do you know any default function or a user contributed function that can draw an ellipse with given axes and origin? Thanks for any help. Paul. -- Romance, like alcohol, should be enjoyed, but should not be allowed to become necessary. -- Edgar Friedenberg -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list --

Dear List, this may be a little off-topic, but I failed to obtain the "mother of R"-reference through a couple of library services... Maybe someone can provide me with a PDF? Ross Ihaka and Robert Gentleman. R: A language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5(3):299-314, 1996 Helmut Schuetz Biokinet GmbH A-1170 Vienna Tel +43(0)1

Dear Stuff, I am trying to enjoy "PAM", but I could not recognize which sample is in which branches in the clustering tree because of too many samples and size limitation for my monitor. I mean, I did unsupervised clustering with "PAM" ( data2$newy<-pamr.makeclasses(data2) ) with 275 primary samples, but samples were piled up at the point of each branch, so I cannot

Hello. I have data (plant weights over time) that are non-linear and in which the variance increases over time. I have to estimate the first derivatives of plant weight given time (i.e. growth rate) and their se, using a regression smoother, and I have been considering cubic spline smoothers. However, I do not know if this can be done given that the error variance would increase over time.

I'm trying to plot four different sorghum types on a plot using a different colour/symbol combination for each sorghum type (TYPBOTA in the script below). What am I doing wrong?: plot(xx$LATITUDE,xx$SFD1, points(xx$SFD1,xx$LATITUDE, col=1:4[codes(xx$TYPBOTA)],pch=c(4,3,1,2)[codes(xx$TYPBOTA)]) grid() I get the following error message Error in 1:4[codes(xx$TYPBOTA)] : NA/NaN argument

as.integer() truncates doubles toward zero, as Splus does (at least v. 6.1 under Windows does). Thus: > look <- (10 * seq(14)) - 76 > 10 * (73.1 + look) [1] 71 171 271 371 491 586 681 791 886 981 1101 1201 1301 1401 > as.integer(10 * (73.1 + look)) [1] 70 170 270 370 490 586 681 791 886 981 1101 1201 1301 1401 ... It is not documented in R! I propose appending

The following code in clusplot.default (package cluster) is in error: x1 <- cmdscale(x, k = 2, eig = TRUE) var.dec <- sum(x1$eig)/sum(diag(x1$x)) if (var.dec < 0) var.dec <- 0 if (var.dec > 1) var.dec <- 1 x1 <- x1$points x1 has components with names "points" and "eig", not "x", so

Greetings, R-Wizards: I'm trying to find an extremum subject to a nonlinear constraint. (Yes, I have perused the archives but have found nothing positive.) The details of the problem are these: In a paper published some years ago in Technometrics, ("Confidence bands for cumulative distribution functions of continuous random variables" Technometrics, 25, 77-86. 1983), Cheng and

This is was something like a request for your comments, thoughts on the topic... Many of you will know that the "..." (aka \dots) argument is very useful for passing ``further graphical parameters'', but can be a pain when itself is passed to too many plotting functions inside your own function. An artificial example being myplot <- function(x,y, ...) { plot(0:1, 0:1,

Hello again, First I want to thank all the people who answered my question about line width in graphs. I promise I will learn the 'par' help page by heart for the end of the month ! I now want to trace some ellipses to emphasize groups of data. I found how to trace circles with 'symbols()', but no ellipse. I'm planning on writing my own function based on

In some contexts, I find the current behavior of rank() very `suboptimal'. We have the argument na.last = {TRUE | FALSE | NA } where the first two cases treating NAs (almost) as if they were == +Inf or == -Inf whereas the 3rd case just drops NAs. For the typical ``Rank Transformation'' that is recommended in EDA in several contexts, I would however want something else, namely keep

R 1.7.1 on Windows XP The "normal Q-Q plot" produced by plot.lm() mislabels points when the model is fitted using na.action=na.exclude. Example: x <- 1:50 y <- x + rnorm(50) y[c(5,10,15)] <- NA # insert some NA's y[40] <- 50 # add an outlier plot(lm(y ~ x, na.action=na.omit)) # outlier correctly labeled in all # four plots