similar to: Complete Linkage Clustering techniques

Dear R I recently performed a cluster analysis. It produced the dendogram no problem but unfortunately the font size of the row.names were all cluttered due to their large size So I tried to change the font size using plclust(cluster.results, labels=iris$specie, cex=0.8) and R came back to me saying Error in plclust(cluster.results, labels = iris$specie, cex = 0.8) : unused argument(s)

Dear R help I have been trying to conduct a chi square test on two groups of variables to test whether there is any relationship between the two sets of variables chisq.test(oxygen, train) Pearson's Chi-squared test data: oxygen X-squared = 26.6576, df = 128, p-value = 1 > chisq.test(oxygen) Pearson's Chi-squared test data: oxygen X-squared = 26.6576, df = 128,

Dear R I recently did a scatterplot matrix using the following command pairs(sleep[c("SlowSleep", "ParaSleep", "logbw", "logbrw", "loglife", "loggest")],col=1+as.integer(ParaSleep > 5.5 | SlowSleep > 15.7)) this highlighted outlying points for some of the x,y plots that I needed to identify. Unfortunately this highlights all the x,y

Dear R What does NaN mean? I recently did a correlation on a batch of data for some reason it didn't like one column cor(sleep,use="complete.obs") BodyWt BrainWt SlowSleep ParaSleep TotalSleep BodyWt 1.00000000 0.95584875 -0.3936373 -0.07488845 -0.3428373 BrainWt 0.95584875 1.00000000 -0.3867947 -0.07427740 -0.3370815 SlowSleep -0.39363729

can you recommend a good manual for R that starts with a data set and gives demonstrations on what can be done using R? I downloadedR Langauage definition and An introduction to R but haven't found them overly useful. I'd really like to be able to follow some tutorials using a dataset or many datasets. The datasets I have available on R are Data sets in package 'datasets':

Hi, I am new at R, and I need some help with some basic stuff. I want to do clustering of data. It works perfectly, but now I want to export my file form R to my Linux directory. The problem is that the file is generated only with the cluster numbers, but it does not carry over the identifiers. Let me show you what I did : 1. demo<-read.table("my_table", sep=",",

> -----Original Message----- > From: Brett Stansfield > Sent: Wednesday, 19 January 2005 4:25 p.m. > To: 'S.Ganesh at massey.ac.nz' > Subject: Document1 > > <<Doc1.doc>> I was trying to get R to analyse one variable of the file > Chicken Weight. when I ask > > hist(data$weight) > R says "x must be numeric" > yet when I

Dear R Can you tell me how to change the working directory of R It's just that I have some text files that I wish to save separately from the R filing structure eg. into C:/my documents and need to change the working directory of R so that it reads these files . This means if I ever upgrade the current version of R nothing will be effected. brett Brett Stansfield Environmental Scientist -

The R function hclust is used to do cluster analysis, but based on R help I see no way to print the actual fusion distances (that is, the vertical distances for each connected branch pairs seen in the cluster dendrogram). Any ideas? I'd like to use them test for significant differences from the mean fusion distance (i.e. The Best Cut Test). To perform a cluster analysis I'm using: x

Dear R, I recently did a canonical correlation analysis on two subsets of data (location and weather). So I now have canonical scores for location and weather. but I'd now like to do a scatterplot matrix using the pairs statement. Is there a way to somehow join location.U and weather.V to become a new data set from which I could undertake a scatterplot matrix of the canonical variates?

I am using R for hierarchical clustering of a number of documents. I have a distance matrix on which I have applied hclust method. When I plot the result of hclust method, I can see the dendogram plotted. What I need now is the dendogram stored as a tree in a data structure. My goal is to automatically label all internal nodes. For that, I need to know, which leaf nodes make a first level

Hi,   I need to generate a heatmap on a square matrix and wouldn't want to reorder the columns and the rows on the heatmap display.    I have used the options Rowv=NULL and Colv=NULL but doesn't seem to work. Following is a snippet of the heatmap function i am using. args <- commandArgs(); inputfile <- args[2] imgfile   <- args[3] bitmap(imgfile, height=15, width=15, res=100,

Hi everyone, I am using the fastgreedy.community function to get the $merges matrix and the $modularity vector. This serves my purpose of testing modularity of my graph. But I am "greedy" to plot the heat map and dendrrogram based on the $merges dendogram matrix. I know that heatplot does the graphics part but I am not sure if the dendogram generated by the heatplot will match the one

Hello everyone! I have two questions regarding cluster analysis with the package 'cluster' : 1. I have a dissimilarity matrix in csv format, and I would like to use it to generate a dendogram using 'hclust'. How do I make that matrix compatible with the function? I think it has to be similar to the objects generated by the 'dist' function. Any ideas? 2. Does

Hi everybody! Anybody knows how can I get detalied information about clusters after using hclust? The issue is that if I have some items in different clusters, I would like to get the cluster where each item is placed. Taking into account that my data set is too large, it is not useful to have the dendogram or a graphic, and really I need something like a simple table with item label and cluster

Dear all, I need to make dendogram from read count in a csv file across 34 samples including biological replicate. Please share R code or package to do this. Do I also need to normalized read count before using read data? Thanks [[alternative HTML version deleted]]

I think are looking for the function 'cutree' from package mva checkout its documentation: > require(mva) > ?cutree pleanty of examples to do what you want. ############################################################################# Hi R lovers! I am using the agnes function of the package cluster to compute a hierarchical clustering. I'd like to know if somebody has ever

I have a data which contain some NA value in their elements. What I want to do is to **perform clustering without removing rows** where the NA is present. I understand that `gower` distance measure in `daisy` allow such situation. But why my code below doesn't work? __BEGIN__ # plot heat map with dendogram together. library("gplots") library("cluster")

When I use the image() function for a relatively small matrix it works perfectly, eg.x <- 1:100 > z <- matrix(rnorm(10^4),10^2,10^2) > image(x=x,y=x,z=z,col=rainbow(3))but when I want to plot a larger matrix, it doesn't really work. Most of the times, it just plot a few intermitent points.x <- 1:1000 z <- matrix(rnorm(10^6),10^3,10^3) image(x=x,y=x,z=z,col=rainbow(3))

I want to do hierarchical cluster analysis to compare 10 groups of vectors with five vectors in each group (i.e. I want to make a dendogram showing the clustering of the different groups). I've looked into using dist and hclust, but cannot see how to compare the different groups instead of the individual vectors. I am thankful for any help. Anders