similar to: Fitting 3 beta distributions

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)

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]

Hello I am trying to find an automated way of fitting a mixture of normal and log-normal distributions 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

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

Hi all, I just installed R on my Mac OS X machine and wanted to installed tcl/tk. So, I installed tcl/tk from this page: http://cran.r-project.org/bin/macosx/tools/ It gets placed in /usr/local dir. and then I installed R. Next, in R, I set the TCL_LIBRARY variable by saying Sys.setenv(TCL_LIBRARY="/usr/local/lib/tcl8.5") and Sys.setenv(TK_LIBRARY="/usr/local/lib/tk8.5") But

> 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

Moved to R-help because there'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

Hi All, I apologise if this question has been answered before, but my background is a little different from most people using R, and the language we use seems to be different! I am trying to analyse some nuclear physics data, which consists of an ensemble of "energy" readings in a detector that, when binned, form a number of Gaussian shaped peaks superimposed on a varying background

I fitted a mixture denstiy of two gaussians two my data. I now want to calculated the standard errors of the estimates via the boot.se command of the mixtools package. My question is now, if the output is correct? It seems a bit odd to me, so is this correct what I am doing and can I rely on the values? My data: http://s000.tinyupload.com/?file_id=09285782882980618119 My code:

I fitted a mixture denstiy of two gaussians two my data. I now want to calculated the standard errors of the estimates via the boot.se command of the mixtools package. My question is now, if the output is correct? It seems a bit odd to me, so is this correct what I am doing and can I rely on the values? My data: http://s000.tinyupload.com/?file_id=09285782882980618119 My code:

I tried to post this question two times, each time it seemed to fail, since " An embedded and charset-unspecified text was scrubbed..." So I try it again: I fitted a mixture density of two gaussians two my data. I now want to caluclate the standard errors of the estimates via the boot.se command of the mixtools package. My question is now, if the output is correct? It seems a bit odd

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 multiple actual

Dear R-helpers: We have had fun using betareg to fit models with proportions as dependent variables. However, in the analysis of these models we found some wrinkles and don't know where is the best place to start looking for a fix. The problems we see (so far) are that 1. predict ignores newdata 2. anova does not work Here is the small working example: ---------------------------- x

Hello, I have a dataset with proportions that vary around a fixed mean, is it possible to use betareg to look at variance in the dispersion parameter while keeping the mean fixed? I am very new to R but have tried the following: svec<-c(qlogis(mean(data1$scaled)),0,0,0) f<-betareg(scaled~-1 | expt_label + grouped_hpi, data=data1, link.phi="log",

Dear all, I get an error using betrag on this data set :http://dl.dropbox.com/u/1866110/dump.csv. I run it like this regression f2.1=betareg(Y~X1+X2,data=dump) summary(f2.1) I get : Call: betareg(formula = Y ~ X1 + X2, data = dump) Standardized weighted residuals 2: Error in quantile.default(x$residuals) : missing values and NaN's not allowed if 'na.rm' is FALSE In addition:

Hi I'm trying to fit a model in betareg and I'm getting errors, but have no idea what they mean or how to solve them. Does anyone have experience with this? > model <- betareg(ACT ~ ST*SoilT, data = actDL_F) Warning messages: 1: In sqrt(W) : NaNs produced 2: In sqrt(W) : NaNs produced 3: In sqrt(1 + phihat) : NaNs produced data summaries don't give any na's or problems I

Folks, The betareg package appears to be polished and works well. But I would like to look at the exact formulas for the underlying model being estimated, the likelihood function, etc. E.g. if one has to compute \frac{\partial E(y)}{\partial x_i}, this requires careful calculations through these formulas. I read "Regression analysis of variates observed on (0,1): percentages, proportions and

Good morning, Does anyone know of a package or function to do a beta regression? Thanks, Walt Paczkowski _________________________________ Walter R. Paczkowski, Ph.D. Data Analytics Corp. 44 Hamilton Lane Plainsboro, NJ 08536 (V) 609-936-8999 (F) 609-936-3733

Dear R users, I'm trying to do betareg on my dataset. Dependent variable is not normally distributed and is proportion (of condom use (0,1)). But I'm having problems: gyl<-betareg(cond ~ alcoh + drug, data=results) Error in optim(par = start, fn = loglikfun, gr = gradfun, method = method, : initial value in 'vmmin' is not finite Why is R returning me error in optim()? What

Hi, I am running some rather complex mixtures of beta regressions using the betamix() command from the betareg package (V. 3.0-4). If I am doing exploratory regressions with only one random starting value (nstart=1) I obtain results which converge after about 100 iterations. However, if I run regressions with nstart=100 random starting values I obtain solutions amended with a warning that no