similar to: mixdist package in R

Dear List, We are using the mix() function in the mixdist package to fit mixture models to some of our data. The package provides a function to compare the fits of nested models using an ANOVA function. However, we were wondering whether there are methods that can be used to compare models that differ in the number of distributions fitted and/or the shape of the distributions. Is there a way,

Hi, All, I want to fit a normal mixture model. Which package in R is best for this? I was using the package 'mixdist', but I need to group the data into groups before fitting model, and different groupings seem to lead to different results. What other package can I use which is stable? And are there packages that can automatically determine the number of components? Thank you, Cindy

Dear R-help, my aim is to fit a constrained 2 component gamma mixture using mix within package mixdist. The constraints being fixing both of the means and both of the sigmas. Thus the only unconstrained parameter I wish to fit is pi the proportions of the mixtures. This is the code I used: PP2Pars<-data.frame(c(0.23,0.77), c(9.174,29.54), c(9.983,12.369));

Hello, I would like to fit a mixture of two Weibull distributions to my data, estimate the model parameters, and compare the fit of the model to that of a single Weibull distribution. I have used the mix() function in the 'mixdist' package to fit the mixed distribution, and have got the parameter estimates, however, I have not been able to get the log-likelihood for the fit of this model

Hi,all with my data,there are more than 1000 quantitative results of antibody concentrations, there may be 2 components(positive and negative), or 3 components (may be strong positive, positive, and negative), or 4-6 components. Could you tell me how to determine the number of components of the mixture model? the "anova.mix" in mixdist of the R software seems not work. my

Hi, All, I have a density function with 3 variables which is defined on some irregular domain, and I want to get the marginal distribution of each variable. Is there any function doing this? A simple example is p(x,y,z)=x*y*z*I(xy>z). So each marginal distribution is a function of the other two variables. My density form is very complicated, so I cannot do it by hand. I was just wondering if

Hi all, I'm trying to install the mixdist package with: install.packages("mixdist") But I'm getting the following errors: * installing *source* package ‘mixdist’ ... ** R ** data ** preparing package for lazy loading ** help *** installing help indices ** building package indices ... Warning in utils::data(list = f, package = package, lib.loc = lib.loc, envir = dataEnv) :

Dear all, I am trying to fit a double gaussian to some data using the mixdist package: --- begin code --- ? library(mixdist) ? time <- seq(673,723) ??counts <- c(3,12,8,12,18,24,39,48,64,88,101,132,198,253,331,419,563,781,1134,1423,1842,2505,374,6099,9343,13009, ? ? ? ? ? ? ? ? ? ?15097,13712,9969,6785,4742,3626,3794,4737,5494,5656,4806,3474,2165,1290,799,431,213,137,66,57,41,35,27,27,27) ?

Hi, I am working on a population of an invasive clam. The data are the size of each clam per station (2mm on average). Each station is found at a different distance from a power nuclear station, so at different water temperatures. The fist step I want to do is to identify cohort size at each station or (zone of water temperature). The second step will be to see whether the size or number of

I fitted a gaussian mixture to my financial data. The data can be found here: http://uploadeasy.net/upload/32xzq.rar I look at the density with plot(density(dat),col="red",lwd=2) this has a skew of library(e1071) skewness(dat) -0.1284311 Now, I fit a gaussian mixture according to: f(l)=πϕ(l;μ1,σ21)+(1−π)ϕ(l;μ2,σ22) with:

Dear R User, I am an electrical engineering student and have just come across a curve fitting problem. I need to find the constituent Gaussian distribution curves fitting the data attached in Workbook1.txt here. I tried to use Mixdist on R but ran into following problem. Can you suggest me where I am going wrong? > super <-read.table("Workbook1.txt",,sep ="\t") >

Dear all, The new version of AdMit (version 1.01-01) is now available from CRAN. SUMMARY The package provides functions to perform the fitting of an adaptive mixture of Student-t distributions to a target density through its kernel function. The mixture approximation can then be used as the importance density in importance sampling or as the candidate density in the Metropolis-Hastings

Dear all, The new version of AdMit (version 1.01-01) is now available from CRAN. SUMMARY The package provides functions to perform the fitting of an adaptive mixture of Student-t distributions to a target density through its kernel function. The mixture approximation can then be used as the importance density in importance sampling or as the candidate density in the Metropolis-Hastings

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

Dear Ingmar & Dave, Thanks a lot for your help and sorry for the late reply. Finally, I've found a way to separate the mixture of distributions (empirically). But the gamlss package looks great, I'm sure it will help me during my further studies. Kind regards, Susanne On 15 Jun 2009, at 20:09, Ingmar Visser wrote: > Dear Susanne & Dave, > > The gamlss package family

Hi, everyone, I need to use a C library. But since I have little experience in C, I want to call this C library in R and program the rest in R. Does anyone know how to do this? Thanks, Cindy [[alternative HTML version deleted]]

Dear all, I am attempting to model some one-dimensional data using a mixture model of non-central Student's t distributions. However, I haven't been able to find any R package that provides this functionality. Could there be a way to "manipulate" the EM algorithms from the mixdist or mixtools package to fit the model, or do you have any other suggestions? If anyone could help

Dear R users, Please help me on using "mix" function under package "mixdist". My data distribution shows there are two components for the mixture distribution: left part is an exponential and right part is a normal. So I plan to use "gamma" mixture distribution to estimate the parameters. Here is what I am using for the "mix" function. Test<-mix(x,

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. I have a finite mixture modeling problem -- for example, a 2-component gaussian mixture -- where the components have a large overlap, and I am trying to use the "mclust" package to solve this problem. I need

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. I have a finite mixture modeling problem -- for example, a 2-component Weibull mixture -- where the components have a large overlap, and I am trying to adapt the "mclust" package which concern to normal