similar to: EM algorithm for truncated multivariate mixture of normals

Hi, I would like to know if it is possible to have a "R code" to estimate the parameters of a mixture of bivariate (or multivariate) normals via EM Algorithm. I tried to write it, but in the estimation of the matrix of variance and covariance, i have some problems. I generate two bidimensional vectors both from different distribution with their own vector means and variance and

Hi, i would to know, if someone have ever write the code to estimate the parameter (mixing proportion, mean, a var/cov matrix) of a mixture of two multivariate normal distribution. I wrote it and it works (it could find mean and mixing proportion, if I fix the var/cov matrix), while if I fix anything, it doesn't work. My suspect is that when the algorithm iterates the var/cov matrix, something

Hi, i would to know, if someone have ever write the code to estimate the parameter (mixing proportion, mean, a var/cov matrix) of a mixture of two multivariate normal distribution. I wrote it and it works (it could find mean and mixing proportion, if I fix the var/cov matrix), while if I fix anything, it doesn't work. My suspect is that when the algorithm iterates the var/cov matrix, something

Please help me in writing the R code for this problem. I've been solving this for 4 days. It was hard for me to solve it. It's a simulation problem in R. The problem is My true model is a normal mixture which is given as 0.5 N(-0.8,1) + 0.5 N(0.8,1). This model has two components. I will get a sample size equal to 100 from this model. I will do this 200 times. That means, I will have

hi i'm looking for a gibbs sampling algorithm for R for the case of mixture of K normals, and in particular for the case of bivariate normals. i'd be grateful if anyone could send its own R-routine, at least for the univariate case. thank you in advance matteo

Hello, I am trying to find out if R can do the following: I have a mixture of normals say f = 0.2*Normal(2, 5) + 0.8*Normal(3,2) How do I find the difference in the densities at any particular point of f and at Normal(2,5)? -- Thanks, Jim. [[alternative HTML version deleted]]

Dear All, I wonder if there is an R package to estimate the generalized linear mixed models but with a random effects having a mixture of normals as a prior distributinon .. Thank you, Abderrahim [[alternative HTML version deleted]]

Dear Friends, Is there an R package which implements regression models with error distributions following a scale mixture of normals? Thanks Anup

All: I am trying to fit a mixture of 2 normals with > 110 million observations. I am running R 2.5.1 on a box with 1gb RAM running 32-bit windows and I continue to run out of memory. Does anyone have any suggestions. Thanks so much, Tim [[alternative HTML version deleted]]

Hello, i need some help concerning the library norm. i habe to impute some missing values using the em algorithm. The help offered for the library doesn't really help me, maybe somebody already worked on em algorithm or multiple imputation. some fictive Data x1 x2 50 60 24 . 26 20 87 . 21 . Problem: Em Algorithm in R calculating the missings in x2. Thanks in advance. -- View this

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Can anyone send me the R code for fitting a mixture of normal distributions. Or in fact any'combination' of mixtures of distributions. I looke dta mix but it is still not clear to me. Jim [[alternative HTML version deleted]]

Hi, I have a problem of estimating a mixture of two normal distributions. I need to find the starting points automatically, since this is a part of a larger piece of image processing code. I found the mix2normal1 function in VGAM package that mentions a method of finding starting values for mu1 and mu2 but refers the reader to a book by Everitt and Hand. Unfortunately, I do not have an easy

Hi, I am currently working on fitting a mixture density to financial data. I have the following data: http://s000.tinyupload.com/?file_id=00083355432555420222 I want to fit a mixture density of two normal distributions. I have the formula: f(l)=πϕ(l;μ1,σ21)+(1−π)ϕ(l;μ2,σ22) my R code is: normalmix<-normalmixEM(dat,k=2,fast=TRUE) pi<-normalmix$lambda[1] mu1<-normalmix$mu[1]

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

Hi, I woul like to know if it is possible to have a "R code" to generate EM Algorithm for a normal bivariate mixture. Best regard, S.F.

Hey, I am confused about how to generate the sample data from a mixture of Multivariate Gaussian ditribution. For example, there are 2 component Gaussian with prior probability of 0.4 and 0.6, the means and variances are u1=[1 1]', Cov1=[1 0;0 1] and u2=[-1 -1]', Cov2=[1 0;0 1] repectively. So how can I generate a sample of 500 data from the above mixture distribution? Thanks. Fred

Hello, I am searching for a way to generate random values from a multivariate mixture distribution. For starters, one could create a mixture distribution consisting of a gamma or normal distribution and then a tail/spike of values in a normal distribution (eg as in Figure 1,?A Eyre-Walker, PD Keightley. 2007. The distribution of fitness effects of new mutations. Nature Review Genetics 8: 610-618)

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),

Hi all, I'm curious if anyone has coded an Expectation-Maximization algorithm that could help me model some circular data I have. I'd like to model it as a mixture of uniform and Von Mises centered on 0, so the only free parameters is the mixing proportion and the kappa of the Von Mises. I couldn't find anything in the contributed packages that seemed to suit this purpose. Any