similar to: prior covariance in Mclust

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

Hi, I'm trying to use the library mclust for gaussian mixture on a numeric vector. The function Mclust(data,G=3) is working fine but the fitting is not optimal and is using modelNames="E". When I'm trying Mclust(data,G=3,modelName="V") I have the following message: Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else ans[orderedNames] : argument is

Hi, I got the same problem like http://tolstoy.newcastle.edu.au/R/devel/04/11/1204.html R crashes when I use the em function from the mclust package on univariate data and on a special case on bivariate data (when the matrix is not provided as written in the manual). It seems as if the problem is the format of the data to be analyzed. Operating System: Windows XP (SP2) R version: R-2.0.1 The

My question is with respect to mCLUST and the values of BIC and log likelihood. The relevant part of my R script is: ######################### BEGIN MDS ANALYSIS ######################### #load data data <- read.table("Ecoli33_Barry.dis", header = TRUE, row.names = 1) #perform MDS Scaling mds <- metaMDS(data, k = Dimensions, trymax = 20, autotransform =TRUE, noshare = 0.1,

Hi All, I need to fit a mutlivariate normal model to a dataset in order to obtain the mean and covariance parameters. I see that the MVN function in the MCLUST package can do this, however when I try to run even the simplest example provided in the documentation, as below, I get the following error: n <- 1000 set.seed(0) x <- rnorm(n, mean = -1, sd = 2) mvn(modelName = "X", x)

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

Hi, I'm trying to use the library mclust for gaussian mixture on a numeric vector. The function Mclust(data,G=3) is working fine but the fitting is not optimal and is using modelNames="E". When I'm trying Mclust(data,G=3,modelName="V") I have the following message: Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else ans[orderedNames] : argument is

Dear R users, I use mclust to fit a mixture of normal distributions to many datasets. Usually the Mclust function finds 1 or two normal distributions, rarely, 3. But I hit a strange case today. my.data <- c(57.96920, 51.79415, 51.20538, 55.53637, 51.64291, 56.61476, 51.28855, 55.56169, 51.85113, 54.03330, 51.37370, 49.48561, 52.41580, 53.51176, 60.49293, 55.77012, 51.59270, 56.29660,

I keep on receiving the message below after submitting the following line using the mclust package. m2 is a 99 X 1 column vector. * em(modelName = "E", m2, mu = c(25, 50), sigmasq=10, pro = c(0.4, 0.6)) Error in as.double.default(data) : (list) object cannot be coerced to double. Why do I receive this error? Thank, Brian C. Newquist Research Statistician

I'm running Mclust 3.0 in R-2.7.0 and have run into a situation where the optimal number of clusters, 12, seems to be greater than the number of colors available to Mclust. The code below, which demonstrates errors, does not if the max no of clusters is set at 10. sessionInfo, after a restart of R and loading of packages, follows the output. Is this a known problem with Mclust? Can I

Dear list members, I am using Mclust in order to deconvolute a distribution that I believe is a sum of two gaussians. First I can make a model: > my.data.model = Mclust(my.data, modelNames=c("E"), warn=T, G=1:3) But then, when I try to plot the result, I get the following error: > mclust1Dplot(my.data.model, parameters = my.data.model$parameters, what = "density")

I'm sorry, this is probably a very simple question. I am relatively new to R and am having difficulty understanding how to use the mclust options to change the prior probabilities for a mixture model. I am dealing with a situation where I have 2 groups of data and it is known that the sample sizes are different in the population. I want to incorporate the probability associated with

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

Hi all, I have to ask this and I know that the reason is that I am a newbie with R programming. So apologize if it is too obvious but I didn't find an answer after googling and reading "An introduction to R". So i have return data from 30 instruments and I am fitting a mixture of normal distributions for the asymmetric marginal distributions and then simulating from those

Hi, I am trying to understand how the functions em() and me() from the mclust package work. I cannot make sense of what the algorithm returns. Here is a basic, simple example: ######################################### # two bivariate normals, centered at (-5,0) and (5,0), with Id covariance x1 = cbind(rep(-5, 100), rep(0, 100)) + matrix(rnorm(100*2), 100, 2) x2 = cbind(rep(5, 100),

I've been trying to install some R packages such as mclust and flexmix on linux but have had the following error messages. > I've been trying to install mclust on my notebook which has linpus linux lite os and I have installed R as well as some packages all right. However, when I tried to install mclust, it gave me the following messages. Any suggestions? Tim ++++++++++++++++

My previous messge to the list follows below this one. I found some garbage at the top of the file 'mclust' in the 'R' subdirectory of the package. I deleted that with BBEdit. The package appears to load properly now, although I have not really tested it. I am not sure to whom to report this. I downloaded the package twice, so this may be a problem with the version stored

Howdy, I'm experiencing a segmentation fault when trying to load mclust.so from mclust-1.1-4. I'm using R-1.3.1 on RedHat 6.2, and `gcc --version` reports "egcs-2.91.66". Any ideas? -Andy Package install: > install.packages("mclust") [stuff omitted] Installing source package `mclust'

To Whom It May Concern: I am new to r and mclust, so this may be a silly question. It has also been a lot of years since I have used unix regularly. I have version 1.7.1 of r, precompiled for Classic Mac OS (I am running 9.2.2 on a PowerBook G4). I downloaded the precompiled version 2.0-2 of mclust for Classic MacOS. The implementation of r appears to be functioning properly (various

While looking at someone's question on this list led me to the mclust package, and from there to its license. Excerpts: Except for strict academic use, use of MCLUST (by itself or through other packages) requires payment of an annual license fee and completion of a license agreement found at the following URL: http://depts.washington.edu/ventures/UW_Technology/Express_Licenses/mclust.php 1.