similar to: Partition data into clusters

Dear R-users, I have the following 2 files; A V1 V2 A 1 A 2 A 3 A 4 B 1 B 4 C 1 C 3 D 4 B V1 V2 process1 1 process2 2 process3 3 process4 4 I want to get this output C V1 V2 V3 A 1 process1 A 2 process2 A 3 process3 A 4 process4 B 1 process1 B

Hi, I have created a heatmap using heatmap.2 having 7 clusters. I would like to extract the list of genes that are in these 7 clusters. Is there any function that can be used to extract genes for each cluster? Cheers, Sudhir -- __________________________________________________________ SAVE PAPER - Please do not print this e-mail unless absolutely necessary Being happy doesn't mean

Hi, I am an R newbie. I am running R2.5.1 on WinXP. I am trying to run a pacakge (BNArray1.0) that depends on deal 1.2-26 and dynamicGraph 0.2.0.1 . These are available on http://www.cls.zju.edu.cn/binfo/BNArray/#OLE9 . I have installed the 3 packages (using local files). When I try to run BNArray, I reveicd this error message > local({pkg <- select.list(sort(.packages(all.available =

Hello. I'm trying to compute median for a filtered column based on other column but there was something wrong. I'll show how I did step by step. Here's the data: a b c class 1 12 0 90 A-B2 3 97 11 A-B3 78 NA 123 A-C4 NA NA 12 A-C5 8 33 2 A-B6 12 NA 0 A-D On the command I typed: 1) data =

Hello. I'm a newbie here. In my script (I name it readData.R), I wrote the followings: readData <-function(){ med = read.csv("medicalData.csv");} Then I tested the script by 'Source R Code' then on the command I typed 'readData()' then I typed 'med' to check if the variable contains the medical data but it returned 'Object med is not found'. What

Hi! Recently I try to find the method maximum likelihood for gamma,weibull,Pearson type III,Kappa Distribution, mixed exponential distribution, skew distribution. I have tried function ms() for gamma two parameters and weibull two parameters.It works but not for Pearson type III. I have problem to find the likelihood function for mixed exponential distribution and kappa distribution. So can

Hi all I am working on k-means algorithm (in R: kmeans( ) ). The R-help advice us to try several random start in order to avoid local minimum. Does one know if there is a procedure that automaticly run this rerolling and select the best partition ? Or any studies that gives clues on the number of rerolling ? Thanks for helping. Christophe

hi r-help, i am doing kmeans clustering in stats. i tried for five clusters clustering using: kcl1 <- kmeans(as1[,c("contlife","somlife","agglife","sexlife",                         "rellife","hordlife","doutlife","symtlife","washlife",                       

Hello all, I am using the clustering functions in R in order to work with large masses of binary time series data, however the clustering functions do not seem able to fit this size of practical problem. Library 'hclust' is good (though it may be sub par for this size of problem, thus doubly poor for this application) in that I do not want to make assumptions about the number of