similar to: "cloud" function doesn't plot

Hi all, I have received the following error from summary.manova: Error in summary.manova(manova.test, test = "Pillai") : residuals have rank 36 < 64 The data is simulated data for 64 variables. The design is a 2*2 factorial with 10 replicates per treatment. Looking at the code for summary.manova, the error involves a problem with qr(). Does anyone have a suggestion as to how to

Could anyone please explain how to set up contrasts between means in R. I want to know if "before I conduct an experiment and believe the mean for 1 and 2 will be different from means 3 and 4, Is this true?" That is what I have to prove or disprove, I thought that contrasts would be the way to go. Thanks for the help. Igor [[alternative HTML version deleted]]

Hi all, I am trying to get a handle on gls (package nlme). I have a toy problem: 3 fixed factors (A, B, C), two levels each, 5 replicates per treatment. The response variable is continuous, normal. I have a correlation matrix of the form: > mat A B C A 1.00 0.75 0 B 0.75 1.00 0 C 0.00 0.00 1 which is common to all observations. How do I construct the call to gls? I think I need to

Hello, can anyome tell me how to access the full script of the panel.smooth function so that I can change the thickness of the smoothing line or its colour ? All I could access is : > panel.smooth function (x, y, col = par("col"), bg = NA, pch = par("pch"), cex = 1, col.smooth = "red", span = 2/3, iter = 3, ...) { points(x, y, pch = pch, col = col, bg =

I am looping over many data files and reading in the data with F <- read.table(filename) to read in a 22000 by 15 matrix. Works fine on the first matrix F, but I get the following error when the second file is read into F: Error in "row.names<-.data.frame"(*tmp*, value = row.names) : duplicate row.names are not allowed I have tried picking a column of the matrix and

Hello, My name is Rodrigo, I am using R program and I have a trouble. I am trying to do a dendrogram with genetics information. Let me explain... The Similarity Matrix was already did, and with this matrix I want to construct a dendrogram. So, the distance is done. I need to transform this matrix (that I have) in a dendrogram, I woud be very grateful if someone could help me. PS: I am sending

dear group members, I am looking for a function that assess the stability of cluster. The result of hclust function is an hclust object which can be plot as a dendrogram. However to have confidence in the tree topology usualy bootstap is applied. I understand that I can apply bootstarp on the original data and then run hclust(dist() ) as much as I resampled but how to comapre the topologies the I

Hi, I'm probably being dense, but could somebody tell me how I can get tick marks on the axes of my wireframe plot to show up? This gets me a beautiful looking plot, but no ticks: wireframe(z ~ x * y, data, drape=T, colorkey=F) Thanks in advance, -James [[alternative HTML version deleted]]

I would appreciate some advice on the following task. I have some data that currently looks like this: t1 <- data.frame(id=c(1,1,2,2), aspect=c("A","B","A","B"), score=c(10,9,11,12)) I'd like it to look like this: id A B 1 10 9 2 11 12 reshape() looks like a good candidate for this job but I'm not really sure about the roles of

Hello I was wondering if it was possible to enter R commands from an external text file. If it is possible, it will be easy for repetetive tasks. Does anyone have an idea ? thanks in advance Ahmet Temiz TURKEY ______________________________________ ______________________________________ The views and opinions expressed in this e-mail message are ...{{dropped}}

Hi, Can someone set me straight as to how to write formulas in R to indicate: complete independence [A][B][C] joint independence [AB][C] conditional independence [AC][BC] nway interaction [AB][AC][BC] ? For example, if I have 4 factors: hair colour, eye colour, age, sex does > mosaicplot( frequency ~ hair + eye + age + sex) mean that the model fitted is of complete independence of

Dear all, So far i could do (in an informal way) to draw a Standardized Resisual plot in the following way- --------------------- >x <- c(104.1, 106.6, 105.5, 107.5, 109.6, 113.3, 115.5, 117.7, 119.9, 122.1, 124.3, 126.5, 128.2) >y <- c(53732, 52912, 57005, 61354, 67682, 71602, 71961, 75309, 82931, 93310, 102161, 103068, 108927) >

Hi R helpers, I was wondering if anybody knows if is possible to generate bootstrap values for a cluster analysis in R. What I am trying to do is obtain some confidence on the clusters formed by resampling the data set. A similar type of analysis is used in molecular taxonomy and the confidence values of each cluster are placed in the nodes of the dendogram. Any ideas on how to do this

I got a shock a few days ago when I accidentally visited www.r-project.com . I thought that the r-project site had been hacked until I realised my mistake. There is also a site www.r-project.net. Both of these sites appear to be Japanese. Does anyone know anything about them? I suppose that it is not unusual for names close to those of popular sites to be used. It is good that they use a

Dear R People: Is there a library for Multivariate time series, please? For some reason, I'm thinking that Dr. Paul Gilbert may have one? R Version 1.6.2 (i've updated!) for Windows Thanks so much! Sincerely, Erin Hodgess University of Houston - Downtown mailto: hodgess at uhddx01.dt.uh.edu

Hello, I do this a=c(10.2,0.4,0.2,5.2,8.6,1.6,0.0,1.0,6.3,1.4,0.4,0.2) b=matrix(a,nrow=4) rownames(b)=c("20/04/2002","21/04/2002","22/04/2002","23/04/2002") colnames(b)=c("p1","p2","p3") barplot(b,beside=T,col=(c("red","orange","yellow"))) then I have

Hi, First ,please excuse my poor English. Can someone help me on reading fortran binary object under R? I was trying to read mm5 data under R. However, I seem to stuck at reading fortran binary file storing met. data array. At the beginning, I used readBin() to read mm5 output directly with the following command. #mmout is a mmout file generated with mm5

Hi all, I'm currently working with a dataset that has quite a few missing values and after some investigation I figured that multiple imputation is probably the best solution to handle the missing data in my case. I found several references to functions in S-Plus that perform multiple imputation (NORM, CAT, MIX, PAN). Does R have corresponding functions? I searched the archives but was not

I have a "list" of character vectors. I'm trying to see if there is a way (in a single line, without a loop) to pull out the first element of all the vectors contained in the list. listOfVectors[1:length(listOfVectors][1] doesn't work. ========================== If you want more details.. Here is my listOfVectors which is called "uuu" >

A student is trying to cluster some data. Tree-building things seem to be pretty hopeless (we've tried most of the ones in R, I think). Multi-dimensional scaling produces somewhat tantalising results: things do clump together somewhat, but the clusters overlap a lot. I was wondering if these was an artefact of squeezing it down to 2D, and whether 3D might be better. So loc <-