search for: statisticiangermani

Hi, I tried to send several questions to the lists (both normal R and R-Sig-Finance), but everytime I look them up in the archives my messages end up with the following "An embedded and charset-unspecified text was scrubbed... for example see my post here: https://stat.ethz.ch/pipermail/r-sig-finance/2013q2/011496.html This one was a real important for me. Can subscribers still read it?

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

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

Hi, I try to understand how the generalized hyperbolic distribution is standardized. One reference is the rugarch vignette, page 16-18: http://cran.r-project.org/web/packages/rugarch/vignettes/Introduction_to_the_rugarch_package.pdf I looked at the code of the dsgh function in the fBasics package: > dsgh function (x, zeta = 1, rho = 0, lambda = 1, log = FALSE) { if (length(zeta) == 3) {

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:

Hi, I want to calculate the Value at Risk with using some distirbutions and a volatility model. I use the following data(http://uploadeasy.net/upload/cdm3n.rar) which are losses (negative returns) of a company of approx. the last 10 years. So I want to calculated the Value at Risk, this is nothing else than the quantile. Since I have losses I consider the right tail of the distribution. Consider

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]

Ok, I try it again with plain text, with a simple R code example and just sending it to the r list and you move it to sig finance if it is necessary. I try to be as detailed as possible. I want to fit a distribution to my financial data using a volatility model to estimate the VaR. So in case of a normal distribution, this would be very easy, I assume the returns to follow a normal distribution