similar to: Clustering techniques using R

I have 316 files storing a number of cycles of the respiratory signal from 316 different patients. Each file record is made up of the following data: amplitude,phase,timestamp,validflag,ttlin,mark,ttlout amplitude: is the position in cm relative to an arbitrary reference (signal amplitude) phase: is the phase value for the current sample (the time point at which the breathing signal was

Hi It is preferable to echo your posts to r-help, you usually get more answers and some definitelly superb to mine. It is also better to start a new mail if your question has nothing to do with original subject "Maura E Monville" <maura.monville at gmail.com> napsal dne 01.10.2007 17:44:43: > Unluckily I do not have the privilege of practising with R all day > long. I

I have a pretty big similarity matrix (2870x2870). I will produce even bigger ones soon. I am using PAM to generate clusters. The desired number of output clusters is a PAM input parameter. I do not know a-priopri what is the best clusters layout . I resorted to the silhouette test. It takes forever as I have to run PAM with all possible numbers of clusters. I wonder whether there is some faster

I tried to install "segmented" from three different repositories but I keep getting the following message on R window: ... Please, advice where to find this package. Thank you in advance. Maura > utils:::menuInstallPkgs() --- Please select a CRAN mirror for use in this session --- Warning: package 'segmented' is in use and will not be installed > utils:::menuInstallPkgs()

Can R handle graphic text ? I mean something like a pop-up message window or a text widget ? Thank you so much. -- Maura E.M

I saw there exists an R version for Mac/OS. I'd like to hear from someone who is running R on a Mac/OS before venturing on getting the following computer system. I am in the process of choosing a powerful laptop 17" MB PRO 2.6GHZ(dual-core) 4GBRAM .... Thank you so much, -- Maura E.M [[alternative HTML version deleted]]

I am reading the comprehensive on-line documentation about msm. The positive side is that it seems it has been designed for biomedical statistics, like Clinical Trials. The bad side is that it does not seem to model observations sequences that are not independent but instead are autocorrelated, as it is my case. I did not find any mention to correlated observations therefore I assume the authors

I have downloaded the source code for Linux. the ./configure procedure can find gcc but cannot find f77 or f2c I have looked for the above compiler with Test and installed all what pertains to Fortran. Still not even the man pages for f77 anf fc2 work >. Where is f77 and f2c with linux 10.3 ?? Thank you do much -- Maura E.M [[alternative HTML version deleted]]

I recently installed R 2.6 on Linux/SuSE When I was running the previous version on Windows I was able to save my plots from a script. There was a command "savePlot" that is no more retrieved in the last version. In this scenario, how can I tell R to save the currently displayed plot to a file ? The "save" command is generic and do not know how to tell R that the plot is to be

R printed out the following error messages during the installation of the package "clusterfly": > *install.packages("clusterfly", repos = getOption("repos"),dependencies =TRUE) *--- Please select a CRAN mirror for use in this session --- trying URL ' http://umfragen.sowi.uni-mainz.de/CRAN/bin/windows/contrib/2.5/clusterfly_0.2.2.zip ' Content type

Thank you for your prompt answer. The breathing signal observations are the amplitude values as a function of time and phase. According to our model the hidden states are the different breathing types. Subjects, whose respiratiion process is regular, are likely to breathe, keeping the same cycle pattern/type, for many consecutive cycles. therefore dwelling in the same hidden state. The more

I have a loop that processes all the raw data files in agiven directory. It should allocate only the memory to accomodate the filenames list. Each file is loaded into RAM one at a time and saved to another directory after processing. The R script runs fine but it had some memory problems so it was terminated before getting to the end of the list. This is a Windows XP desktop with ~ 1GB RAM In the

I am reading some documentation about Cross Spectrum Analysis as a technique to compare spectra. My understanding is that it estimates the correlation strength between quasi-periodic structures embedded in two signals. I believe it may be useful for my signals analysis. I was referred to the R functions that implement this type of analysis. I tried all the examples which generated a series of

Sorry for my silly questions. I'm a beginner with R and most statistics concepts. I carried out a simple linear regression where the dependent variable is explained through a combination of powers of cos(independent variable). I can see R returned a good R^2 factor (> 0.99) but I have a hard time at interpreting all the other info that R prints out by using summary( regression.results),

I have downloaded and tried to install JGR - Java GUI for R - Version 1.5. I followed all the instructions (at least in my best resolution) and installed Java latest version. R installation complete fine. Has anyone succeded in installing JGR on SuSE 10.3 ? In the following I hade detailed the failed installation, As root /i did the following: linux-Mimin:/usr/local/bin # ./R R version 2.6.0

I have 316 files. Each file represents a patient's breathing track (respiratory signal recorded for a variable number of cycles). All files have the same are made up of a header followed by a variable number of records. Each record contains 7 comma separated fields. The patient ID is recorder in the header which is stripped off when reading the file into a R data.frame. Since I need to keep

I am downloading the latest R source code R-2.6.1.tar.gz I am installing ion a 64-bit machine. Is the configuration script the proper one for 64-bin installation ? I mean the compiler and linker options ..? Thanks you, Maura -- Maura E.M [[alternative HTML version deleted]]

I'd like to know why I cannot get a plot and the QQnorm in the same sheet. The commands are simple but: library(nlme) glmod1 <- gls(upfmla,correlation=corAR1(),method="ML") summary(glmod1) par(mfrow = c(2,1)) plot(glmod1, main="GLS Residuals vs. GLS Fitted") qqnorm(glmod1) No matter what (I tried different permutations of the plotting commands) the second drawing

I am going to try out a tentative clustering of some feature vectors. The range of values spanned by the three items making up the features vector is quite different: Item-1 goes roughly from 70 to 525 (integer numbers only) Item-2 is in-between 0 and 1 (all real numbers between 0 and 1) Item-3 goes from 1 to 10 (integer numbers only) In order to spread out Item-2 even further I might try to

I would like to install the package "growth" as it contains the function "corgram" and some other presumably useful stuff for time series analysis. I can see it is in R standard library list: http://hosho.ees.hokudai.ac.jp/~kubo/Rdoc/doc/html/packages.html<http://hosho.ees.hokudai.ac.jp/%7Ekubo/Rdoc/doc/html/packages.html>