similar to: Help with normal distributions

Hi All, I am trying to cluster a one-dimensional data (see the file attached) using Mclust() but got an error message like: >Mclust(x) Error in rep(1, n) : Object "n" not found When I do a simulation sometimes it works sometimes doesn't. >Mclust(c(rnorm(50),rnorm(56,-0.5))) Error in rep(1, n) : Object "n" not found >Mclust(c(rnorm(56),rnorm(56,-0.5))) best

Dear group, I want to use the mclust package on large data, and therefore I want to use a subset in the initial clustering phase. From help(mclust): k: If `k' is specified, the hierarchical clustering phase will use a sample of size `k' of the data in the initial hierarchical clustering phase. The default is to use the entire data set. m2 is a

Dear Christian, first of all thank you for your answer. I am going to parse through the pages you told me. Meanwhile I'd like to note that probably it is a good idea to put 2-3 lines of R-code demonstrating such a simple needs somnewhere in docs of `cluster' package. E.g. x<-rnorm(500) ... # output means we have rather 1 claster x<-c(rnorm(500), rnorm(500)+5)

Hi all, once more about the old subj :-) My data has too much various distribution families and for every particular experiment I need just to decide whether the data is "quite homogeneous" or it has two or more clusters. I've revisited the following libraries: amap, clust, cclust, mclust, multiv, normix, survey. And I didn't find any ready-to-use general

Hello all (especially MCLUS users). I'm trying to make use of the MCLUST package by C. Fraley and A. Raftery. My problem is trying to figure out how the (model) identifier (e.g, EII, VII, VVI, etc.) relates to the covariance matrix. The parameterization of the covariance matrix makes use of the method of decomposition in Banfield and Rraftery (1993) and Fraley and Raftery (2002) where

Dear R-users, I have a two - dimensional data set which needs to be clustered into groups: I'm searching for groups of points which show a positive correlation (in a twodimensional plot of the data set), but I do not have any knowledge about how many groups there might be. Do you know of a clustering algorithm in R (or in general) which can use a-priori information about the cluster's

Dear Knowledgeable R Community Members, Please excuse my ignorance, I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance. I have a finite mixture modeling problem -- for example, a 2-component gaussian mixture -- where the components have a large overlap, and I am trying to use the "mclust" package to solve this problem. I need

Hi, I would like to know if someone knows an extended implementation of k-means in R to find appropriate number of clusters for a given k-dimensional data. Also, I am working on clustering for forecasting, if someone is interested or has knowledge on implementational details please mail me, I would appreciate it. Regards Skanda Kallur "Cogito, ergo sum" (I think, therefore I

I'like to do cluster analysis by using mahalanobis distance. Could you tell me how to do?

Dear All, Does anybody know if there is a functionality in R to break histograms that show a clear bi-modal (or multi-modal) distribution into a series of unimodal histograms that added up result in the original histogram? I was thinking of using QQ-plots (for which tools are available in R), and then observing the number of times the observed quantiles cross the 1:1 line, but this only gives an

Are there any S-Plus or R libraries/packages that do Finite Mixture Analysis following the algorithms similar to those implemented in Geoffrey MacLachlan's EMMIX program? Thanks. Dr. Marc R. Feldesman email: feldesmanm at pdx.edu email: feldesman at attglobal.net fax: 503-725-3905 "Don't know where I'm going. Don't like where I've been. There may be no exit. But

Hi people, Does anybody know some Density-Based Method for clustering implemented in R? Thanks, Fernando Prass _______________________________________________________

Hello everyone. I have a few MCLUST questions and I was hoping someone could help me out. If you’re an MCLUST user, they will likely be pretty easy to answer. Thanks in advance for any help. Ken What are the pros/cons of starting a finite mixture model at the “m” step versus the “e” step (where “m” is the maximization step and “e” is the expectation step of the EM algorithm)? In

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Dear useRs, I have a curve which is a mixture of Gaussian curves (for example UV emission or absorption spectrum). Do you have any suggestions how to implement searching for optimal set of Gaussian peaks to fit the curve? I know that it is very complex problem, but maybe it is a possibility to do it? First supposement is to use a nls() with very large functions, and compare AIC value, but it is

Dear list, Can anyone provide a package or code for estimating the parameters of a mixture of c (c >=2) univariate normal distributions? I've tried the algorithm provided by Venables & Ripley (1999) p 263, for the mixture of two normal, but I don't find the "ms" function in R. I've used nls instead, but I'm not sure if it works the same. The data I have is very

Hello list! I would like to fit a distribution to each of the peaks in a histogram, such as this: http://photos1.blogger.com/blogger/7029/2724/1600/DU145-Bax3-Bcl-xL.png . The peaks are identified using Petr Pikal peaks function ( http://finzi.psych.upenn.edu/R/Rhelp02a/archive/33097.html), but after that I am quite stuck. Any idea as to how I can: Fit a distribution to each peak Integrate the

Dear Developers: I have a question about memory management in R 2.2.1 and am wondering if you would be kind enough to help me understand what is going on. (It has been a few years since I have done software development on Windows, so I apologize in advance if these are easy questions.) ------------- MY SYSTEM ------------- I am currently using R (version 2.2.1) on a PC running Windows 2000

<FONT face="Default Sans Serif, Verdana, Arial, Helvetica, sans-serif" size=2><div>I was wondering if anyone knew there are functions to do mixture modeling in R.</div><DIV>&nbsp;</DIV><DIV>Many thanks in advance,</DIV><DIV>Peter

Hey, Dose R include some package for Gaussian Mixture Model data generation and parameters estimation? Now I want to assign lots of multivariate data into a GMM model. So just wondering if given sample data, can we use some functions to estimate the compoents' density function. Thanks for your support. Fred -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-