similar to: mclust: modelNames("E") vs modelNames=("V")

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 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 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

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,

Hello, I am using the parameterized EM- Algorithm in clustering context. I use generated datasets, containing 5000 points in 20 dimensions with 5 clusters. The following poses a problem for me: emEst<-me(modelName="EEV",data=data[,1:numDimensions],z=unmap(x)) emEst<-me(modelName="VEV",data=data[,1:numDimensions],z=unmap(x)) coordProj(main="Model

Hi all, I am using the package ChIPpeakAnno, and I have a problem with the function getAllPeakSequence. This is related to object oriented programming I think, I have the following message: > peaksWithSequences <- getAllPeakSequence(peakList, upstream = 100, > downstream = 100, genome = Hsapiens) Error in validObject(.Object) : invalid class "GRanges" object: superclass

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

Hello I want to batch job the calculation of many GLM-models, extract some values and store them in a file. Almost everything in the script below works (read file, extract values and write them to file) except I fail in indexing the GLM with the modelstructure it should run. Running GLM's conventionally is no problem. Conventionally a GLM is calculated as:

Hi All, I have a n x m matrix. The n rows are individuals, the m columns are variables. The matrix is in itself a collection of 1s (if a variable is observed for an individual), and 0s (is there is no observation). Something like: [,1] [,2] [,3] [,4] [,5] [,6] [1,] 1 0 1 1 0 0 [2,] 1 0 1 1 0 0 [3,] 1 0 1 1 0 0 [4,] 0 1 0

I suppose everybody who makes a package for the first time thinks "I can change anything!" and then runs into this same question. Has anybody written out information on how a package can override functions in R base in the R 2.14 (mandatory NAMESPACE era)? Suppose I want to alphabetize variables in a summary.data.frame, or return the standard deviation with the mean in summary output.

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@biostat.ku.dk # ###################################################### I stumbled on this error while doing a classroom demonstration. The error is reproducible,

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

I'm moving this part of an on-going discussion to r-devel because I think I've uncovered a bug: >summary.default : How is yours different from R's (I didn't try to find out) > If it has an advantage you should post to R-devel as a proposal I did propose it along time ago, but ... The fix was for a bug that Splus 3.2 and 3.3 have. It does not work properly with lists

Hello sir: Here's the result of repeated measures ANOVA. $"Error: Within" Df Sum Sq Mean Sq F value Pr(>F) t 2 524177 262089 258.24 1.514e-06 *** Residuals 6 6089 1015 --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 My question is: How to extract the F value only? If the result is a

Greetings. I've written a convenience function for multicollinearity diagnosis. I'd like to report to the user the formula that is used in a regression. I get output like this: > mcDiagnose(m1) [1] "The following auxiliary models are being estimated and returned in a list:" [1] "`x1` ~ ." formula(fmla)() [1] "`x2` ~ ." I'd like to fill in the period

Hello, I'm trying out flexmix and mclust for the first time on some univariate data which is typically best described as lognormal, but can sometimes be gamma distributed as well. I first tried using EM on mclust assuming the data was lognormally distributed and could only get it to work in "E" mode, i.e. the equal variance mode. I could never get it to work on "V" mode [

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 All, I am using em() function to estimate a poisson-gaussian process from a univariate one dimension time series, but not sure how to do. In the help manual, it specify that in "pro" of the argument "parameter", if the model includes a Poisson term for noise, there should be one more mixing proportion than the number of Gaussian components. But in the example, the parameter

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 regarding parameters in 2 functions in the "mclust" package. -------------------- PROBLEM DESCRIPTION -------------------- I have a finite mixture modeling problem -- for example, a 2-component gaussian

I am new to r and mclust. 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. It appears (from the example I was using below) that I need a library called lapackLib. There does not appear to be a precompiled version at CRAN. There is a makefile for lapackLib, to use with MPW.