similar to: posterior probability in finite mixture

Dear Listers, My post might be somewhat OT. Currently, I am trying to use flexmix to build a finite mixture model. For instance, I am getting the prior probability and coefficients for each latent class from training data. Is there a way to get the posterior probablity and prediction of a new dataset? What I am thinking is to apply the prior prob and coefficient from training set to testing data

Dear All, I finally have chance to have R install on our unix server. However, the system admin asked me if I prefer command-line or gui interface. I have experience with R on linux before but never use R on unix. Here are my questions that I need you guys help. 1) is there a good gui for R/unix like we do for windows and mac? 2) if the answer for 1) is yes, which one is better interms of

Dear All, Is there a emacs/xemacs for unix without compiling it? If it is possible, I prefer something that I can use immediately after putting it on the unix server. Is it possible or am I too stupid to ask this kind of question? Thanks for your insight! -- =============================== WenSui Liu ChoicePoint Precision Marketing Phone: 678-893-9457 Email : wensui.liu at choicepoint.com Blog

Dear R users: I am wondering how to ask for *fixed* number of distributions under parameterized Gaussian mixture model. I know that em() and some related functions can predict the parameterized Gaussian mixture model. However, there seems no parameter to decide number of distributions to be mixed (if we known the value in advance). That is, assume I know the (mixed)data is from 3 different

Dear Lister, plot() is using the data range as the default limits of yaxis. Is there any way I can change the limits? I just look at the help of plot() and par() and couldn't find answers. Thanks. -- WenSui Liu (http://spaces.msn.com/statcompute/blog) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center

Sometimes, it is too costly to read the whole data file into R. I am looking for solution in scan() and read.Lines() but don't they work. Thank you so much! -- ============================== WenSui Liu Acquisition Risk, Chase Blog : statcompute.spaces.live.com Tough Times Never Last. But Tough People Do. - Robert Schuller

Dear Listers, Is there any good paper about how to use R together with VB? Thank you so much! -- WenSui Liu (http://statcompute.blogspot.com) Senior Decision Support Analyst Cincinnati Children Hospital Medical Center [[alternative HTML version deleted]]

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

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

Dear Lister, Is there an interface in R with SQL server that allows me to append records to table in the DB? Might I do that using RODBC? Thanks a lot. -- WenSui Liu A lousy statistician who happens to know a little programming (http://spaces.msn.com/statcompute/blog)

Dear Listers, I have 2 questions regarding xml. 1) how to read/write tables in xml? 2) compared with csv, is xml a better way to transfer data cross systems/applications? Thank you so much for your insight. -- WenSui Liu (http://statcompute.blogspot.com) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center [[alternative HTML

IHi all, have a dataset with rows as plots and environmental data as columns. I have predicted the values using the following ed.pred<-predict(lda.ed,ed) #lda.ed the model, ed the env. variables used for the prediction plots I am wanting to know the formula used by predict.lda for calculating the posterior probabilities. Can anyone point me in the right direction? Thanks

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

With predict.lda the posterior probabilities only relate to the existing Class definitions. This is fine for Class definitions like gender but it is a problem when new data does not necessarily belong to an existing Class. Is there a classification method that gives posterior probabilities for Class membership and does not assume the new data must belong to one of the existing Classes? A new

Do we have any R package that can do analysis on finite mixture model with logistic regression? Thanks Faith Feng Gao Dept. of Statistics Virginia Tech. Email: fgao at vt.edu

Hi, Is there any package that I can use to simulate the Gaussian Mixture Model , which is a mixture modeling method that is widely used in statistical learning theory. I know there is a mclust, however, I think it is a little bit different from my problem. Thanks very much.. regards. -------------------------- Peng Jiang ?? Ph.D. Candidate Antai College of Economics &

Can anyone point me to a comparision of the various packages avaliable to do Finite Mixture Models or Latent Class Models in R. As ever my googling only produce papers on specific packages or implementations. I am looking of a considered comparision that criticlaly compares them. Failing that just your own opinion or experience would be nice to hear. Best R

Dear R-users, I would like to use the package flexmix to fit latent classes to a regression model. My data are repeated measurements of bernouilli variables so I can use the binomial family link to the glm function. The design is not balanced, meaning that for some individuals in my data set I have 10 measurements or more, for others I only have 5 or even less. My question is the following. Can

Are there any S-Plus or R libraries/packages that do Finite Mixture Analysis following the algorithms similar to those implemented in Geoffrey MacLachlan's EMMIX program? Thanks. Dr. Marc R. Feldesman email: feldesmanm at pdx.edu email: feldesman at attglobal.net fax: 503-725-3905 "Don't know where I'm going. Don't like where I've been. There may be no exit. But

This question teeters on the brink of general statistics rather than an R-specific issue, but I'm hoping it boils down to how I coded V&R's EM algorithm for finite mixture modeling and not something worse (i.e. that my plan is impossible). Briefly, I'm trying to simulate an experiment where the hypothesis concerns bimodal vs. unimodal distributions, in order to see what