similar to: newbie (me) needs to model distribution as two overlapping gaussians

Hi! I need to fit a data that shows up as two gaussians partially superimposed to the corresponding gaussian distributions, i.e. data=c(rnorm(100,5,2),rnorm(100,-6,1)) I figured it out how to do it with mle or fitdistr when only one gaussian is necessary, but not with two or more. Is there a function in R to do this? Thank you very much in advance, Luis

Dear R Users?? I woould like to generate mixture model data. I try two type method as followings two method, can anyone tell me which is right? or better? 1. generate two vectors data y1 and y2 from f1 and f2 seperately, and calculate y=alpha1*y1+alpha2*y2, 2. generate prob=unif(1), if prob <alpha1 y=y1, else y=y2. Can anyone give me some idea? Thanks so much! Goeland goeland at

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 R users, I would like to know wether there exists a package or routine within the R environment which allows to test for multiple Gaussians in a given distribution: I have a histogram of some variable which seems to be tri - or at least bimodal, so I would like to test if this is significant to some level and/or estimate the underlying possible distributions. Thank you very much, Yours

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

I have not followed the history of this thread, but I am quite flummoxed as to why the OP is rewriting code to estimate parameters from an univariate Gaussian mixture model when alternatives such as EMCluster (which generally appears to handle initialization better than MClust) exist. Or perhaps there is more to it in which case I apologize. But I thought that I would make the OP aware of the

hi all! i want to mix a dataset that is build up from 2 distribution: an exponential and a normal. I can' figure out how can i use Rmix package to do the fitting of my data. Pheraps it si the wrong package? any suggestion? thanks, nelson

Full_Name: Kamil Barto? Version: 2.8.0 OS: windows xp Submission from: (NULL) (212.33.92.187) According to the "deparse" function documentation "nlines" is the *maximum* number of lines to produce. But, when "nlines" argument is supplied, it produces exactly nlines of result, and the result contains empty elements at the end. Example: >

Hi, I have been trying to figure out how to use the nonlinear regression to fit the cumulative lognormal distribution to a number of data points I have but I am a new R user and I cant quite decipher the notes on nonlinear regression. Any help in this regard will be greatly appreciated, my email address is mmiller at nassp.uct.ac.za

Hi, I'm trying to fit a hidden Markov model (mixture of Gaussians) to stock prices (Open, High, Low, Close) data. Here's my code: #First download the data with package TTR library(TTR) n <- 200 data <- getYahooData("GOOG", strftime(as.POSIXlt(Sys.time() - n*24*3600),format="%Y%m%d")) keep <-

Is the matrix exponential available in some package? The cannonical reference is "Nineteen dubious ways to take the exponential of a matrix". (Love that title) Terry T.

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

> On Aug 23, 2016, at 11:30 PM, Sanjoy Das <sanjoy at playingwithpointers.com> wrote: > > Hi Wei, > > I've not seen GCC's SCEV so I cannot make a comparative comment here > (maybe Chris, Andy or Dan can chime in here), but I personally am in > the "make the cleanup passes smarter" camp. We can also try to make > SCEV expansion smarter -- not by

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

Hi fellow users I have a new R problem i am hoping to get some pointers on. I have a dataset that is approximately normally distributed but with a fat left tail. I am interested in a good measurement on how much fatter the left tail is than can be expected from a normal distribution. One thing I'll tried was fitting a two component mixture model with the Rmix package but i am also interested

Hi all, I'm giving a talk in a few days to a group of psychology faculty and grad students re the R statistical language. Most people in my dept. use SAS or SPSS. It occurred to me that it would be nice to have a few concrete examples of things that are fairly straightforward to do in R but that are difficult or impossible to do in SAS or SPSS. However, it has been so long since I have used

Is there a package or function for multivariate garch model in R? I am having a hard time in locating one. Thanks for help in advance. -Young [[alternative HTML version deleted]]

Is there any implementation in R for finding the phase shift between two continuous signals. I would like to find the average phase shift for tow signals over two years. thanks Stephen -- Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted

Dear R users, Simply my question is that how it is possible to generate some random numbers using rnorm( ) but in log transformed values. Thank you, Tobias --------------------------------- [[alternative HTML version deleted]]

I have a thirty thousand row data frame imported from excel and a 60,000 row data frame imported from excel. they share a common subset of the same data and I would like to combine the two into one data frame merged together on the data in common. I have looked at the help file for merge and intersect and cbind and rbind etc... And I can't figure it out. Thanks in advance Stephen --