search for: mixtool

I am trying to install mixtools on Debian Etch and get the following error dell-2 /usr/lib # R CMD INSTALL mixtools_0.1.0.tar.gz * Installing *source* package 'mixtools' ... ** libs gcc -I/usr/share/R/include -I/usr/share/R/include -fpic -g -O2 -std=gnu99 -c new_svalues.c -o new_svalues.o gfortran -fpic -g -O2 -...

Hello, Can the x and y axis limits be specified in a density plot with the mixtools package for a finite mixture model? Uncommenting the xlim2/ ylim2 lines in the plot command below generates 'not a graphical parameter' warnings (and does not change the axis settings), and uncommenting the xlim/ylim lines generates a 'formal argument "ylim" matched by multi...

Hello all, May be silly question, but what exactly is beta parameter in functions like regmixEM from mixtools package? I mean, how to determine this beta, if i have a set of metrics for each case? Is there a function for that? I have try to put NULL at this parameter, but function just do not work in this case. Cheers, Dima [[alternative HTML version deleted]]

I have 2 questions concerning the EM algorithm. Is it true that the EM algorithm gives unique answers for the means and variances of a mixture of 2 normals? I am using mixtools and I am surprised that it works better than a Bayesian program I wrote. If so can someone say why the mixing probabilities are so good? -- Thanks, Jim. [[alternative HTML version deleted]]

Hi, I want to fit 3 beta distributions to my data which ranges between 0 and 1. What are the functions that I can easily call and specify that 3 beta distributions should be fitted? I have already looked at normalmixEM and fitdistr but they dont seem to be applicable (normalmixEM is only for fitting normal dist and fitdistr will only fit 1 distribution, not 3). Is that right? Also, my data has 26

...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 me out, I would be extremely grateful. Kind regards, Susanne Balzer **************************** Susanne Balzer PhD Student Institute of Marine Research N-5073 Bergen, Norway Phone: +47 55 23 69 45 susanne....

...utions to data which is clearly bimodal. Here's a simulated example: x.1<-rnorm(6000, 2.4, 0.6)x.2<-rlnorm(10000, 1.3,0.1)X<-c(x.1, x.2) hist(X,100,freq=FALSE, ylim=c(0,1.5))lines(density(x.1), lty=2, lwd=2)lines(density(x.2), lty=2, lwd=2)lines(density(X), lty=4) Currently i am using mixtools and just run: library(mixtools)mixmdl = normalmixEM(X, k=2, epsilon = 1e-08, maxit = 1000, maxrestarts=20, verb = TRUE, fast=FALSE, ECM = FALSE, arbmean = TRUE, arbvar = TRUE) plot(mixmdl,which=2)lines(density(X), lty=2, lwd=2) This is obviously not the best way of doing this. The estimates it giv...

...variety of distributions and > a function to combine > them into mixtures. In particular, the 3 parameter student's t and the > 4 parameter generalized t > distribution. > > Hth, Ingmar > > On 15 Jun 2009, at 17:12, David Hunter wrote: > > > Hi Susanne. The mixtools package does not do this automatically and > > I would be surprised if there were any package that does. However, > > it's not in principle too difficult to write code to implement an EM > > algorithm to search for a maximum likelihood estimator in a finite > > mixture...

...onfined in a closed interval. Since there are already several packages for EM, I would like to extend one of these instead of writing a new script from scratch. What would be the best way to customize such an existing package for doing that? Which one is the best in terms of extensibility? (e.g mixtools, flexmix ..) -- Giovanni L. Ciampaglia PhD Student University of Lugano, MACS Lab

...- - - - - 0 1 0 0 1 0 0 1 1 1 1 If x = 3, it?s current value is 0 but it?s new value with the Gaussian weighting around would be something like .1*0+.5*1+1*0+0.5*0+.1*1= 0.6 I want to be able to play with adjusting the variance to different values as well. I?ve found wkde in the mixtools library and think it may be useful but I have not figured out how to use it yet. Any tips would be appreciated. Thanks! -- View this message in context: http://www.nabble.com/Weighting-data-with-normal-distribution-tp22728289p22728289.html Sent from the R help mailing list archive at Nabble.co...

Dear R-Users, I have a large number of data(54000) and the field of data is 50 to 2.0e9. I want to use normalmixEM (package:mixtools) to fit them in finite mixture narmal distributions,but get some mistakes.I don't know which steps make the error. I have used the following functions before >x<-read.table("data") >log.x<-log10(x$V1) >log.x<-sort(log.x) >outx = normalmixEM(log.x,arbm...

...ere's no obvious financial content. Michael On Sat, Apr 6, 2013 at 10:56 AM, Stat Tistician <statisticiangermany at gmail.com> wrote: > Hi, > I want to implement the EM algorithm manually, with my own loops and so. > Afterwards, I want to compare it to the normalmixEM output of mixtools > package. > > Since the notation is very advanced, I used LaTex and attached the two > screenshots I also attached the data. Alternatively, the data can be found > here:http://uploadeasy.net/upload/py6j4.rar and the screenshots here: > http://uploadeasy.net/upload/9i04.PNG >...

...res separately. Then I want to combine the results of two glm models with a parameter beta. For example, beta * F(p1) + (1-beta) * F(p2) where F(p1) is a learned model for feature set p1 and F(p2) is the learned model for feature set p2. Is there any way to do that in R? There is a package called mixtools which can fit a mixture of two regression models but it does not separate the features. I would also like to separate features and fit a model for each feature set and then combine them. Thanks, Andra

...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 in order to compare it to the single distribution. I have also had a look at the 'Mixtools' and 'Flexmix' packages. With both of these it is possible to fit a mixture of distributions, but, as far as I can tell, these are pre-defined and do not have a function for a mixture of two Weibull distributions. I have used the 'fitdistrplus' package to fit the single distrib...

Hi, Is there a way I can view the functions source code of a package I installed in my PC. For example I downloaded the great "mixtools" package. I want to see the source code of one of its function "normalmixEM" Is there a way to do it? Presumably from R command prompt? I tried to take a look at the zip file, but somehow I can't seem to find the file on which I can find the source code. Please advice. - Gund...

> 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

...models, WALD, F-test or likelihood ratio-test (LR-test)? My colleague thought that the LR-test would be the best to use, but he was not sure. And in that case which function is best to use. I have found some LR tests but they use fits from glm models etc. Here is an example of my problem. library(mixtools) x.1<-rmvnorm(40, c(0, 0)) x.2<-rmvnorm(60, c(3, 4)) x.3<-rmvnorm(100, c(0, 0)) X.1<-cbind(rbind(x.1, x.2),x.3) colnames(X.1) =LETTERS[1:4] sample A and B is bivariate and C and D is not, so theoretically the best combination would be to use A and B in the model since they change at...

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]]

Dear R-help, I am doing clustering via finite mixture model. Please suggest some packages in R to find clusters via finite mixture model with continuous variables. And also I wish to verify the distributional properties of the mixture distributions by fitting the model with lognormal, gamma, exponentials etc,. Thanks in advance,  warm regards,Ms.Karunambigai M PhD Scholar Dept. of Biostatistics

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