similar to: Fit a mixture of lognormal and normal 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]

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

Dear List, I have read that a lognormal mixture model having a pdf of the form f(x)=w1*f1(x)+(1-w1)*f2(x) fits most data sets quite well, where f1 and f2 are lognormal distributions. Any pointers on how to create a function that would produce the 5 parameters of f(x) would be greatly appreciated. > version _ platform i386-pc-mingw32 arch i386 os

Dear All, Consider the following code: pdf(file="figure.pdf",family="URWPalladio") curve(dlnorm(x,0,1.5),0,10,xlim=c(0,10),ylim=c(0,0.85),axes=F,xlab="",ylab="f") segments(exp(-1.5^2),0,exp(-1.5^2),dlnorm(exp(-1.5^2),0,1.5),lty="dashed") segments(1,0,1,dlnorm(1,0,1.5),lty="dashed")

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

Hopefully an easy one, how do I merge two or more SQL query results? Example: result1 = find_by_sql(x) result2 = find_by_sql(y) What is the best way to merge result1 and result2? I want to be able to reference the objects as if they were obtained via one query. Cheers, Dan

Dear Group, I am having a function that I am running in a loop that generated two results for each loop The result1 is a zoo object The result2 is a data frame Now I want to put both of them in a list or some structure ... that I can access or output to a file after the loop is done. For e.g. for (i in 1:20){ niceFunction(x[i],i) } niceFunction (x,i) { result1 = someOperations() #zoo

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

Thank you for your help in advance. I am trying to pull some data back from a web service library(httr) sample2 <- GET("https://elevation.mapzen.com/height?json={\"range\":false,\"shape\":[{\"lat\":40.7,\"lon\":-76.5}]}&api_key=mycode") result2 <- content(sample2) height <- result2$height[[1]] I would like to put by own latitude

On Sep 24, 2013, at 12:40 PM, Michael Spencer <bigcheesegs at gmail.com> wrote: > On Tue, Sep 24, 2013 at 12:33 PM, Rui Ueyama <ruiu at google.com> wrote: > Hi LLD developers, > > I'm about to make a change to invert the return value of Driver::parse() to return true on success. Currently it returns false on success. > > In many other functions, we return true

On Sep 24, 2013, at 4:07 PM, Sean Silva <chisophugis at gmail.com> wrote: > On Tue, Sep 24, 2013 at 4:17 PM, Nick Kledzik <kledzik at apple.com> wrote: > > On Sep 24, 2013, at 12:40 PM, Michael Spencer <bigcheesegs at gmail.com> wrote: > >> On Tue, Sep 24, 2013 at 12:33 PM, Rui Ueyama <ruiu at google.com> wrote: >> Hi LLD developers, >>

Dear List, Shouldn't result1 and result2 be equal in the following case? Note that log$RequestID is a factor. That is, is.factor(log$RequestID) yields TRUE. result1 <- tapply(log$Flag,factor(log$RequestID),sum) result2 <- tapply(log$Flag,log$RequestID,sum) Yet, when I summarize the output, I get the following: summary(result1) Min. 1st Qu. Median Mean 3rd Qu.

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 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

I've seen some questions regarding the output of multiple objects from a function, however the suggestions all end up suggesting the use of return(list(result1=result1, result2=result2 , result3=result3)). How can I return multiple objects that are 2 big to be added to a list? -- View this message in context:

Hello everyone, What is the most efficient & simpliest way to convert all components of a list to separate columns in a matrix? Is there an easy way to programmatically "pad" the length of the resulting shorter character vectors so that they can be easily combined into a data frame? I have the following code that stores the 2 compoents (of differing lengths) in the same character

I am trying to plot a lognormal density curve on top of an existing histogram. Can anybody suggest a simple way to do this? Even if someone could just explain how to plot a regular normal density curve on top of an existing histogram, it would be a big help. Also, is there some way to search through the R-help archives other than simple browsing? Thank you so much. Your help and time is greatly