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...ction in the survey package (although this error appears not to be specific to svydesign). I am passing parameters incorrectly but am not sure how to correct the problem. ## Call the main function PS.sim (one of mine). The dots are parameters I omitted to simplify the question. ## y.col, str.col, clus.id, and PS.col are names of columns in the object pop. PS.sim(pop=small, y.col="NOTCOV", ...,str.col="new.str", clus.id="new.psu", PS.col="PS.var", ...) ## A data.frame called sam.dat is generated by PS.sim. Its first 3 lines are: ID new.str PS.var...

...rix. I would like to know the row number of RESA matrix's value in DATA matrix. For example, RESA[1,1] = -2.0314185 and its row number in DATA matrix is 1. RESA[1,3]=4.9131070 and its row number in DATA matrix is 10. Is there a simple way to know the row number? I > clus col1 col2 col3 col4 col5 [1,] 1 1 1 1 1 [2,] 2 2 0 2 1 [3,] 2 1 1 2 2 [4,] 1 2 2 1 2 [5,] 3 1 2 2 3 [6,] 3 3 0 3 2 [7,] 1 3 2 0 0 Second, I want to count columns of each row withou...

...orrectly use cl_ensemble and cl_agreement (package: clue). Here is what I am trying to do: library(clue) ## Let p1..p4 be four partitions of the kind p1=c(1,1,1,2,2,2,3,3,3) p2=c(1,1,1,3,2,2,3,3,2) p3=c(1,2,1,3,1,3,1,3,2) p4=c(1,2,1,3,1,3,1,3,2) Each object within the partitions is assigned to cluster 1,2,3 respectively. Now I have to create a cl_ensemble object, so that I can calculate the Rand index: ens <- cl_ensemble(list=c(p1,p2,p3,p4)) which only leads to "Ensemble elements must be all partitions or all hierarchies." Although I understand that p1..p4 are vectors in thi...

Dear people, I've spent some time trying to find a simple way to do the following. I can certainly think of complicated ways to do it... I have a data set of 99 columns and 2000 rows. Each row corresponds to an individual item of data, each column corresponds to a variable. I want this data to be read into a data frame. The first 66 columns are binary, values 0, 1, and I want these to be

Dear people, A somewhat clueless question follows: I just discovered that the lme function in contrib package nlme for R, while similar to the lme function in Splus, does not use the cluster function option. This difference does not appear to be documented in the V&R `R Complements' file. I have data which is divided into 6 groups The lme model is of the form (simplified from the actual model a bit) y = a + b x_{ij} + \alpha_i + \beta_i x_{ij} + \epsilon_{ij} i = 1,...,...

Dear R-listers, I do clustering on tens of individuals by thousands of traits. I have known the assignment of each individual. I want to classify the individuals by randomly resampling different subsets of the traits, for example, randomly resampling 100 traits for 100 times, then 200 traits for 100 times, then 300 traits f...

...'trt', 'trig')] d[d==-9] <- NA d[,c(4,5,7)] <- lapply(d[,c(4,5,7)], FUN=as.factor) str(d) summary(d) --------------- Second, since there is missing data for several (but not all) of the variables, investigate the patterns. --------------- library(Hmisc) na.pattern(d) clus <- naclus(d, method='complete') par(mfrow=c(2,2)) naplot(clus, which='all') print(clus) detach(package: Hmisc) --------------- After examining the missing data patterns, impute 10 datasets using the amelia function from the Amelia package. Check the densities of the continuous v...

Hi, can anyone help me fit betabinomial model to the following dataset where each iD is a cluster in itself , if i use package aod 's betabinom model it gives an estimate of zero to phi(the correlation coeficient ) and if i fix it to the anova type estimate obtained from icc( in package aod) then it says system is exactly singular. And when i try to fit my loglikelihood by wr...

Hi! I have a question concerning the rcdk package: I generated a test sdf-file with 3 molecules in it and tried to perform clustering by fingerprints and plot the results in a dendogramm. This is what I did: mols <- load.molecules ("molecules.sdf") fp.list <- lapply (mols, get.fingerprint, 'maccs') fp.dist <- fp.sim.matrix (fp.list, method='tanimoto') fp.dist <- as.dist(1-fp.dist= cl...

Hi: I have calculated the Silhouette score and Dunn score after hierarchical clustering for 3 clusters: #Distance measure d <- dist(USArrests, method = "euclidean") #Hierarchical clustering hc <- hclust(dist(USArrests), "ave") #calculating silhouette value for 3 clusters sil<- silhouette(cutree(hc, k=3), d) #calculating Dunn index for 3 clusters clu...

...555 b0009 -0.013334 0.046154 b0010 0.952128 0.143617 suppose you have these data into a data frame called myseqs [see the R documentation in how to upload these data, you can try > myseqs <- edit(read.table()) ] # you need to load the necessary libraries library(mva) # basic clustering library(cluster) # more clustering algorithms # then you need to calculate the 'distances' between sequences myseqs.d <- dist(myseqs) # this creates the euclidean distance matrix, try help(dist) for more info # then we perform a hierarchical cluster myseqs.clus <- hclust(m...

Hi All, Mysql service is going down continously in my system due to lack of memory space. I checked the messages log and found the following error message. All mbuf clusters exhausted, please see tuning(7). I have no idea about mbuf cluster. Can anyone please help me to fix the issue. I hope the information below will help you. Following is the output of top. last pid: 84718; load averages: 2.56, 2.29, 2.55 up...

Puede que no me haya expresado certeramente. Es lo que pasa al tocar de oído. Tengo unos datos (df) de los que se alguien calculó unas distancias (dis.df) de las que se hicieron/hacen unos clusters (plot.clus.dis.df). Todo esto usando un programa on line al que no tengo acceso para ver cómo hace los cálculos. Yo tengo los datos, y el programa también me da la matriz de distancias. Quiero, además, tener los clusters (no el dibujo, si no el elemento: elemento <- hclus(dis.df)) Pero el e...

...when upgrading: Is there an easy way to take the libraries I have been using in the older version and pull then into the new version. My organization looks like this on Solaris 2.5.2: /opt -- /R -- /R-0.62.1 --/library -- subdirectories for lots of packages like: MASS, clus, lme, VR, date, design, mva WaveThresh, splines, acepack, eda, stepfun,etc. -- /R-0.62.2 --/library -- base, mva, eda, stepfun I would like to move the other libraries from /opt/R/R-0.62.1/library to /opt/R/R-0.62.2/library and install them. Doe...

Maybe the following article is of interest for you (co-authored by P.J. Rousseeuw, like the book you mentioned): http://www.jstatsoft.org/v01/i04/paper/clus.pdf -Heinrich. > -----Urspr?ngliche Nachricht----- > Von: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] Im Auftrag von Fucang Jia > Gesendet: Donnerstag, 11. Dezember 2003 14:37 > An: r-help at stat.math.ethz.ch > Betreff: [R] Paper on PAM a...

Hello, In cluster analysis with cluster, how does one colour the silhouette plots ? For example in using pam. There seems to be some problem there. Everything else can be coloured. Thanks, A. Mani Member, Cal. Math. Soc

...sc_gs at vsnl.net>, <r-help at stat.math.ethz.ch> > Message-ID: > <4702645135092E4497088F71D9C8F51A128BAF at afhex01.dpi.wa.gov.au> > Content-Type: text/plain; charset="iso-8859-1" > > It's not so much a problem, as not working the way you expected. > cluster:::plot.partition is used to do the plotting. If you look at the > code for this you can see the difficulty in putting every possible > permutation into the code. If for example you want the silhouette plot to > be red using col = "red" is not intuitive as the cluster plot (whi...

Hi R-helpers I have a dataframe DF (lets say with the variables, y, x1, x2, x3, ..., clust) containing relatively many 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 cova...

I am using R 1.3.0 on Windows 2000. For an experiment, I am wanting to find the most diverse 400 items to study in a possible 3200 items. Diversity here is based on a few hundred attributes. For this, I would like to do a clustering analysis and find 400 clusters (i.e. different from each other in some way hopefully). From each of these 400 clusters, I will pick a representative. I expect many of these clusters will have just one item. I am planning to do this using a variety of different clustering methods. What I a...