similar to: Question about plot.mona {cluster}

Hi I have a problem using the package cluster on my binary data. I want to try mona at first. But i get the an error. hc<-read.table("all.txt", header=TRUE, sep="\t", row.names=1) srt(hc) `data.frame': 51 obs. of 59 variables: $ G1p : int 2 1 1 1 1 1 1 1 1 1 ... $ G1q : int 1 1 1 1 1 1 1 1 1 1 ... $ G2p : int 1 1 1 1 1 1 1 1 1 1 ... $ G2q : int 1 1 1 1 1 1

Asterisk work does not pay all of my bills, so I have joined up with a company that has a very good payment plan. I have recently become a Mona Vie Independent Distributor. I am not going to go into a sales pitch. This is just an FYI to this opportunity. The company has grown into a Billion dollar company in just 2 years. This company's compensation plan is the best and quickest that I have

How to Paint Mona Lisa with MS Paint <http://arts-artists.blogspot.com/2007/03/how-to-paint-mona-lisa-with-ms-paint.html> Amazing Art work<http://arts-artists.blogspot.com/2007/03/how-to-paint-mona-lisa-with-ms-paint.html> http://arts-artists.blogspot.com/2007/03/how-to-paint-mona-lisa-with-ms-paint.html --~--~---------~--~----~------------~-------~--~----~ You received this message

Hi! I am trying to calculate a dissimilarity matrix using daisy. The matrix vectver is binary as i test with: > levels(as.factor(vectver)) [1] "0" "1" But the call to daisy gives me the following error message.: > dfl1 <- daisy(vectver, type = list(asymm = c(1:length(vectver[,1])))) Error in daisy(vectver, type = list(asymm = c(1:length(vectver[, 1])))) : at least

Hi all, Is there a way of plotting a 'decision tree' from the results of Mona in the cluster package. The default bannerplot is not quite what I'm after - I would like a plot of the binary decision tree. Thanks Zoë [[alternative HTML version deleted]]

Regarding Tengfei Yin's post about an error trying to install "cluster" in 2.13.0, I have gotten an error with this package when trying to install the released version of 2.12.0. Here is the output on an Ubuntu Linux system: begin installing recommended package cluster * installing *source* package 'cluster' ... ** libs make[3]: Entering directory

Dear R-users, If I would like to track the date when an R-object (specifically an R- function) was modified, how can I achieve that? Furthermore, how can I sort these objects based on date modified? Your help is greatly appreciated All the best Mona -- ***************************************************** *Dr. Mona Kanaan * *Department of Epidemiology

Hello all, So I am using the (formula entry) method for randomForests: randomForest(y~x1+x2+...+x39+x40,data=xxx,...) but the issue is that some of the items in that package dont take a formula entry - you have to explicitly state the y and x vector: randomForest(x=xxx[,c('x1','x2',...,'x40')],y=xxx[,'y'],...) Now my question is whether there is a function/way

Hello there, I'm trying to do lots of plots in one for-loop. But somehow ggplot does not evaluate arguments as expected. Here is an example: library(lattice) library(ggplot2) pl <- list() pl2 <- list() cDat <- as.data.frame(cbind(x1=0:100,x2=0:10,x3=1:20)) for(obs in c("x1", "x2")) { pl[[obs]] <- xyplot(cDat[,obs] ~ cDat[,"x3"], main=obs)

I need some help understanding how on of the example data sets is formatted in the basic R installation. If I load the Mona Loa CO2 data, with the command: > data(co2) I can view the data with: > co2 And the data are in the form of 11 rows labeled as years (1994-2004) and 12 columns labeled (Jan - Dec). This structure appears to be a dataframe, however, if I type the command

I'm puzzled by the following problem, which appears when attempting to run an analysis on part of a dataset: If I try: csubset <- dat$Diagnosis==0 cont <- lme(fixed=cform, random = ~1|StudyName, data=dat,subset=csubset,na.action=na.omit) Then I get: Error in eval(expr, envir, enclos) : Object "csubset" not found But if I do

You might find this useful. I have modified the R 'edit' function by adding attr(x,"date.modified") <- substring(Sys.time(),1,19) before the last line. I then changed to ls() to sort functions, paste function name and time stamp from the contents of the "date.modified" attribute before output. Not particularly tidy but functional.

I feel the need to apologize for my previous email to the list. I was thinking that I was sharing something that I am currently exited with, with my associates. I now realize that I was sooo... off-topic, it's ridiculous. Sorry for the improper post to the list. Feel free to keep any further comments, concerning my improper use of the list, off-list. Thank You, Steven B TeamVie at

Dear R experts, I have a labeled data set. Each data is assigned a binary label 0 or 1. Assume that I use some clustering algorithm to group the data by clusters (using some features of the data). Now I want to know how many data are labeled as 0/1 in each cluster. For example, assume that I have 9 labeled data grouped into three clusters. The ids of the clusters are 1, 2, and 3. The dataset is

if i were to have a block size of 4 people and i want to assign a treatment combination to the entire block, there would be 16 different treatment combinations (TTTT, TTTP, TTPP, PTTP, etc.) i am trying to get all 16 permutations and i am able to use this code below. drugs=c('P','T'); comb=expand.grid(drugs,drugs,drugs,drugs) for a block size of 3 the code would be

Hi dear all It's the first time for me to install a developmental version of R, I came across following errors, my system is DISTRIB_ID=Ubuntu DISTRIB_RELEASE=10.04 DISTRIB_CODENAME=lucid DISTRIB_DESCRIPTION="Ubuntu 10.04.1 LTS" I downloaded the dev version of R in cran R source, and downloaded the recommended packages by using wget as described in R manual, and run

I had installed R from source on Fedora Core 3. Then I upgraded to Fedora Core 4, but left R alone. R worked fine, until I trued to update.packages(). Even then, many packages updated just fine, but two of them, cluster and mgcv, failed with the following error message (using cluster as an example): gcc -shared -L/usr/local/lib -o cluster.so clara.o daisy.o dysta.o fanny.o meet.o mona.o pam.o

Doing the normal build process [1] for a first time with a R 2.0.0 snapshot -- the Sep 21 version I uploaded to Debian's 'experimental' section two days ago, ended in failure. The package in question is cluster 1.9.6 which should be 2.0.0-ready. The (partial) log follows: ----------------------------------------------------------------------------- [...] g77 -mieee-fp -fPIC -g -O2

Hi, I have just found this forum, and it looks like a great place to get some help (I hope) For my dissertation, which is due way too soon, I am doing a survey, comparing attitudes of 2 independent groups, with 5 scale likert questions. Basically I want to show if they have similar or different attitudes. I am testing 4 hypotheses, and have in total about 20 questions. I have to say my

Hi all, Sorry for the re-post, I sent my previous e-mail before it was complete. I am trying to model seroprevalence using the differential equation: dP/dt = beta*seronegative*.001*(seropositive)-0.35*(0.999)*(seropositive)-r*seropositive. I would like to estimate my two parameters, beta and r, using maximum likelihood methods. I have included my code below: