search for: cluste

Dear R users, I'd like to ask u whether you know how to sort out the following: I'm trying to reproduce a dataset of clusters, and for that I need to build up a cluster index (inside a function) using the command "replicate" as follows: dataset<- function( clusters=100, cluster.size=50, outcome.mean=list(mean=3, sd=1), outcome.var=list(mean=0, sd=1), treat=1, unbal = FALSE){ if(clusters%%2!=0) stop(&quot...

Hello everyone I tried to use clust function using "hclustWard" clustering method The distance mesaured I have used is "rf" The data used is in the form of data frame (it is not a distance matrix) - sd.df The piece of code I have used is: c1 <- clust(sd.df,k=6,method="hclustWard",distMethod="rf") But I get the following error message...

...any NAs. When I fit an ordinal regression model with the function lrm from the Design library: model.lrm <- lrm(y ~ x1 + x2, data=DF, x=TRUE, y=TRUE) it will by default delete missing values in the variables y, x1, x2. Based on model.lrm, I want to apply the robust covariance estimator using a cluster variable: model.robcov.lrm <- robcov(model.lrm, cluster=clust) How can I remove observations in the cluster variable clust that contain NAs in y, x1, and x2? Thanks, Christof

...similarity. I assume this can be achieved by specifying the "h" argument with the specified similarity, e.g.: clust<-hclust(dist,"average") cut<-cutree(clust,h=0.65) Now, I would like to draw rectangles around the branches of the dendrogram highlighting the corresponding clusters, as is done by the function rect.hclust(). How can I achieve this with the ouput of cutree? I would appreciate your help! Best regards, Madeleine

Dear list, I have two dissimilarity matrices, one for a training data set which I then clustered using PAM. The second is a diss matrix for a validation data set (an independent field sample). I have been trying to use knn to distinguish distances between the validation data set and the 6 mediods of the training data defined by using PAM. I continue to get error messages in regards to eith...

...command reports an error. I have created a consensus tree using the consensus comand from phylo but cannot manipulate the phylo object afterwards to create a dendogram , by transforming the phylo object into a hclust object and then into a dendogram ?? Thanks for any help library(ade4) library(cluster) library(stats) library(ape) data<-read.table(file="in.matrix",header=FALSE,sep="\t",row.names=1) dis<-dist.binary(data,method=5,diag=TRUE) clust<-hclust(dis) tree1<-as.phylo(clust) tree2<-as.phylo(clust) tree3<-as.phylo(clust) tree4<-as.phylo(clust) tree5...

Hello, I have a large data set that has more columns than rows (sample data below). I am trying to perform a partitioning cluster analysis and then plot that using pca. I have tried using CLUSPLOT(), but that only allows for 'princomp' where I need 'prcomp' as I do not want to reduce my columns. Is there a way to edit the CLUSPLOT() code to use 'prcomp', please? # sample of my data PRVID,VAR1,VAR2,V...

Hi: I have tried to find the appropriate clust algorithm for mixed type of data. The suggested way I see is: 1. use daisy to get the dissimilarity matrix 2. use PAM/hclust by providing the dissimilarity matrix, to get the clusters but by following this, when the data set grows bigger say 10,000 rows of data, the dissimilarity matrix will be O(n^2), and out of memory will occur. I am wondering is there any better ways to do the mixed type cluster? Cheng Yi [[alternative HTML version deleted]]

Problem with join to Active Directory [root@clust-master samba]# net ads join -S 10.0.0.1 -U Administrator Administrator's password: [2006/05/22 10:24:05, 0] libads/ldap.c:ads_join_realm(1640) ads_add_machine_acct (clust): Type or value exists ads_join_realm: Type or value exists [root@clust-master samba]# kinit Administrator@COROD.LOCAL Password for Administrator@COROD.LOCAL: As you can

...t. I can't seem to find information on how to change the default output of a "hanging" style tree with the axis on the right to a left-to-right plot with and axis on the bottom. Example code follows: library(vegan) #loads the "vegan" module that compuptes ANOSIM library(cluster) community <- read.csv("ANOSIMmites.csv", header=TRUE) #reads the data file into memory under the name "community" enviro <- read.csv("ANOSIMenv.csv", header=TRUE) #reads the grouping variables into memory attach(enviro) attach(community) community.dist <-...

Hello, Can someone point me to documentation or ideas on how to calculate the centroids of clusters identified with hclust ? I would like to be able to chose the number of clusters (in the style of cutree) and then get the centroids of these clusters. This seems like a quite obvious task to me, but I haven't been able to put my hands on a relevant command. Thank you, Moritz

...en I install the package and I try an example: --- 8< -------------- library(kml) dn <- as.cld(gald()) kml(dn) # XXX ~ Fast KmL ~ # Erreur dans as.vector(x, mode) : argument 'mode' incorrect --- 8< -------------- So I make some verifications: --- 8< ---- class(dn) # [1] "ClusterizLongData" # attr(,"package") # [1] "kml" getMethod("kml","ClusterizLongData") # Method Definition: # # function (Object, nbClusters = 2:6, nbRedrawing = 20, saveFreq = 100, # maxIt = 200, trajMinSize = 2, print.cal = FALSE, print.traj = FALSE, #...

...22-r2) and second is Opteron (Gentoo linux, x86_64, 2.6.22-r2). Servers are connected by ethernet, adapters are both Intel EtherExpress1000. Firstly, I compiled ocfs2 modules, which is provided with kernel and then I downloaded and compiled ocfs2-tools (1.2.6). In accordance with manual I made file cluster.conf, loaded modules and mounted /config and /dlm. On both systems external array is /dev/sdb, so I made linux partition /dev/sdb1 and ocfs2 filesystem on it. Cluster is started by command # /sbin/o2cb_ctl -H -n clust -t cluster -a online=yes on both servers. If I mount filesystem on one server,...

...the snippet from the check results: ### Begin snippet checking examples ... ERROR Running examples in 'rioja-Ex.R' failed. The error most likely occurred in: > ### * chclust > > flush(stderr()); flush(stdout()) > > ### Name: chclust > ### Title: Constrained hierarchical clustering > ### Aliases: chclust plot.chclust bstick.chclust > ### Keywords: cluster hplot > > ### ** Examples > > data(RLGH) > diss <- dist(sqrt(RLGH$spec/100)^2) > clust <- chclust(diss) > bstick.chclust(clust, 10) Loading required package: vegan Warning in library(pack...

hi all, i'm trying to plot a dendrogram with labeled leaves >rownames(f)<-v.names >v<-rowMeans(f, na.rm=T) >clust<-hclust(dist(v)) >dend<-as.dendrogram(clust,hang=0.05) >clust2<-cut(dend, h=0.5) >class(clust2$low[[1]]) >[1] "dendrogram" then >plot(clust2$low[[1]],horiz=TRUE,frame=F,type = "tr")) but my leaf labels do not fit

I have a quick question, and I apologize in advance if, in asking, I expose my woeful ignorance of R and its packages. I am trying to use the bootcov function to estimate the standard errors for some regression quantiles using a cluster bootstrap. However, it seems that bootcov passes arguments that rq.fit doesn't like, preventing the command from executing. Here is an example: e<-bootcov(rq(y~x),clust,B=10,fitter=rq.fit) (where clust is my clustering variable) results in Error in rq.fit.br(x, y, tau = tau, ...) : un...

...egression analyses on the data. After attaching the data, this is the code I use for tables for four variables (sweight is the weight variable): > a <- xtabs(sweight~research.area + gender + a2n2 + age) > tmp <- ftable(a) Is this correct? I don't think I need to use the strata and cluster variables, right? And, below is the logistic regression code that I use for randomly sampled, or unweighted, data: > logit.1 <- glm(var4 ~ var3 + var2 + var1, family = binomial(link = > "logit")) > summary(logit.1) But how can I do the same analyses for the weighted data?...

Hi all, When setting auth mechanisms: plain login cram-md5 and only having pam passdb and passwd userdb. dovecot nevers starts and crashes reporting: Feb 29 10:19:41 pitux-clust-op1 dovecot: Dovecot v1.0.10 starting up Feb 29 10:19:41 pitux-clust-op1 dovecot: auth(default): CRAM-MD5 mechanism can't be supported with given passdbs Feb 29 10:19:41 pitux-clust-op1 dovecot: Auth process died

ESTE SCRIPT FUNCIONA PERFECTAMENTE, LA PREGUNTA QUE HACÍA SE REFERÍA A QUE SI SERÍA POSIBLE QUE EN LA PROPIA TABLA CSV PUDIERAN ESTAR LOS NOMBRES DE LOS ANTIBIOTICOS Y QUE EL ANÁLISIS PCA NO LO RECHACE POR SER CUALITATIVO, QUE DE ALGUNA MANERA SE DIERA UNA INSTRUCCIÓN PARA EVITAR TENER QE HACER LO DE rownames manualmente setwd("D:/Public/Documents/R/FactoMineR/") table1 <-

I am having trouble getting a covariance matrix for each cluster which is output by kmeans(). My input looks like: > imagedat <- read.table("table", header=TRUE) > imagedat Red Green Blue 0_0 5 7 8 1_0 5 5 18 2_0 7 8 49 3_0 22 8 76 4_0 54 10 67 5_0 50 9 28 6_0...