similar to: mclust package installation is preparing for lazy loading and never finishes

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 ++++++++++++++++

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'

Hi, all; I got an unusual error while using mclust library 2.1-7 on R 2.0.1. When I tried to run Mclust(rnorm(100)), I got segmentation fault error. Does anyone know what causes this problem? I came across the same problem even when I tried to run the example shown in Mclust help using iris data. Thanks in advance, Tae-Hoon Chung -------------------------------------------------- Tae-Hoon Chung

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.

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

I'm trying to test a method of identifying individuals (birds) based on measured data (their calls). I have test data from known individual birds, and I am using the Mclust package to see if the program can correctly identify which calls come from different birds. So far, mclust has correctly ID'd the number of birds in the test data set (i.e., the correct # of clusters). However I

Hi, All; I tried to use library mclust in 64-bit compiled R 2.0.1 but failed. Installation went smoothly without any warning or error. However, when I tried to use them with the following simple code, it crashed. Library(mclust) Dat <- c(rnorm(20, mean=0, sd=0.2), rnorm(30, mean=1, sd=0.2)) Ind <- Mclust(dat, 1, 5)$classification cbind(Dat, Ind) The error message was:

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'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 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

When loading mclust, it shows a license agreement message. This message shows up in my document when I use Sweave. I did the following: <<echo=FALSE,include=FALSE>>= library(mclust) @ Is this a problem with mclust, Sweave or with me? How can it be fixed? Thanks for any suggestions! Titus

Dear All, I have spatial data (presence/absence for 4000 squares) on 250 bird species and would like to use a model-based clustering technique to test for species associations. Is there any way of passing a distance/correlation matrix to mclust as with hclust, rather than the actual data? Or alternatively, is there a way of getting mclust to handle binary data? I'd appreciate any

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")

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

> No HTML this time. Sorry Dear all, I am attempting to model some one-dimensional data using Gaussian mixture model with mclust.? Generally, the data that I have have 3 overlapping populations (with one of them being the majority, and the other two combining to less than 15%) and for some reason, mclust consistently ignores the smaller peaks, giving me strange values for the means

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 an ordered vector of values. The distribution of these values can be modeled by a sum of Gaussians. So I'm using the package 'mclust' to get the Gaussians's parameters for this 1D distribution. It works very well, but, for input sizes above 100.000 values it starts taking really forever. Unfortunately my dataset has around 4.6M values... My question: is it

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 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 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