search for: fraley

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 Sig...

Hello All... I gave a task to my students that involved using mclust to look for clusters in some bivariate data of isotopes vs various mining locations. They discovered something I didn?t expect; the data (called tur) is appended below. p <- qplot(x = dD, y = dCu65, data = tur, color = mine) print(p) # simple bivariate plot of the data; looks fine mod1 <- Mclust(tur[,2:3]) mod1$G mod2

I've put all ``current'' add-on packages into CRAN's source/contrib tree and created an INDEX file (attached below). As you can see, currently we have acepack bootstrap ctest date e1071 fracdiff gee jpn snns splines survival4 (Yes, e1071 and jpn are new ... more on the latter in a later mail.) In the near future, I am hoping for the following: oz (Bill

...re. Do you know enough about the > clustering algorithm (I don't) to know if this kind of analysis would > involve mindbogglingly large matrices that would choke any system? > Its hard to say from the information you give. I would suggest you read the technical reports produced by Fraley and Raferty which are freely available from the Univ. of Washington Stats Dept. web site. Most recently, is their Technical Report 380 entitled "Model-Based Clustering, Discriminant Analysis, and Density Estimation." In part to answer your question, it isn't a matter or R versus...

.... Struyf, A., Hubert, M. and Rousseeuw, P.J. (1997). Integrating Robust Clustering Techniques in S-PLUS, Computational Statistics and Data Analysis, 26, 17-37. (mclust) D. Banfield and A. E. Raftery, Model-based Gaussian and non-Gaussian Clustering, Biometrics, 49:803-821 (September 1993). C. Fraley, Algorithms for Model-based Gaussian Hierarchical Clustering, Technical Report No. 311, Department of Statistics, University of Washington (October 1996), to appear in SIAM Journal on Scientific Computing. *************************************************************************** -.-.-.-.-.-.-....

...ods   base      other attached packages: [1] ensembleBMA_5.0.3 chron_2.3-42      loaded via a namespace (and not attached): [1] tools_2.15.1     Anna Freni Sterrantino Department of Statistics University of Bologna, Italy via Belle Arti 41, 40124 BO. ________________________________ Da: Chris Fraley <fraley@washington.edu> Inviato: Giovedì 12 Luglio 2012 17:42 Oggetto: Re: ensembleBMA pit function warnings Dear Anna Freni Sterrantino,       I'll get to this as soon as I can. I'm still maintaining ensembleBMA because there is no one else to do it, but my time at the University...

...at http://www.stat.washington.edu/www/research/reports/2006/tr504.pdf The main feature in terms of new functionality is the option to include a Bayesian prior in the mixture model for regularization. The older version is still available mclust02 for those who need backward compatibility. Chris Fraley Department of Statistics University of Washington _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages

I am trying to follow the mclust examples in "MCLUST: Software for Model Based Clustering, Density Estimation and Disriminant Analysis" by Chris Fraley and Adrian Raftery, but I cannot reproduce the density and uncertainty surfaces for the Lansing Woods maples. I am using R 1.8.1 with the code below. The same code works fine in S-Plus 6.2 Am I missing something or is this a bug? Thanks Mike White library(mclust) data(lansing) # R only maples&...

Hi: I'm clustering a microarray dataset with a large # of samples. I would like your opinion on the best way to automatically determine the optimal # of clusters. Currently I am using the "cluster" package, clustering with "clara", examining the average silhouette width at various numbers of clusters. I'd like opinions on whether any newer packages offer

...Now is there some switch I can use to prevent this from happening? We do have Samba 3.0.9 with ACL (Standard SuSE Samba RPM) running here. Any hints/help would be greatly appreciatet. Best regards Patrick -- *************************************** COMsulting Gerhard Faehling GmbH Patrick W. Fraley Oeverdieker Weg 6 23669 Timmendorfer Strand Tel: 04503 / 7033-25 Fax: 04503 / 7033-13 E-Mail: pf@comsulting.de Internet: www.comsulting.de ***************************************

...the covRobust contributed package at http://cran.r-project.org/src/contrib/PACKAGES.html#covRobust An Splus version is also available on the S archive of Statlib http://lib.stat.cmu.edu/S/ under the function name cov.nnve cov.nnve is by Naisyin Wang and Adrian Raftery, with contributions by Chris Fraley. References: Wang, N. and Raftery. A.E. (December 2002). Nearest-neighbor variance estimation (NNVE): Robust covariance estimation via nearest-neighbor cleaning (with Discussion). Journal of the American Statistical Association 97(460): 994-1019. Wang, N. and Raftery. A.E. (2000). Nearest-neig...

...the covRobust contributed package at http://cran.r-project.org/src/contrib/PACKAGES.html#covRobust An Splus version is also available on the S archive of Statlib http://lib.stat.cmu.edu/S/ under the function name cov.nnve cov.nnve is by Naisyin Wang and Adrian Raftery, with contributions by Chris Fraley. References: Wang, N. and Raftery. A.E. (December 2002). Nearest-neighbor variance estimation (NNVE): Robust covariance estimation via nearest-neighbor cleaning (with Discussion). Journal of the American Statistical Association 97(460): 994-1019. Wang, N. and Raftery. A.E. (2000). Nearest-neig...

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

Hello, I have a concrete statistical question: I have a sample of an univariate mixture of an unknown number (k) of normal distributions, each time with an unknown mean `m_i' and a standard deviation `k * m_i', where k is known factor constant for all the normal distributions. (The `i' is a subscript.) Is there a function in R that can estimate the number of normal distributions k

Hello All, I have a 131072x132 matrix for which I need to compute a regular euclidean distance matrix, which I then need to transform and run agnes() on this transformed matrix. I am having trouble computing the distance matrix as it is fairly large and I am sure I have gone over the max. The specific error I am getting is: Error in vector("double", length) : negative length vectors

I've only begun investigating R as a substitute for SPSS. I have a need to identify for each CASE the closest (or most similar) 5 other CASES (not including itself as it is automatically the closest). I have a fairly large matrix (50000 cases by 50 vars). In SPSS, I can use Correlate > Distances to generate a matrix of similarity, but only on a small sample. The entire matrix can not