search for: hyperbolic

How to use the package generalized hyperbolic distribution in order to estimate the four parameters in the NIG-distribution? I have a data material with stock returns that I want to fit the parameters to. -- View this message in context: http://r.789695.n4.nabble.com/Generalized-Hyperbolic-distribution-tp3504369p3504369.html Sent from the R h...

Hi, I want to fit standardized generalized hyperbolic distribution to my data. I am aware, that I can do this with the dsgh command of the fBasics package along with the optim command. My problem is, that I also want to have a derivation of it. So I need the theory behind it, i.e. I need the formula of the probability density function which they use a...

Hi, I want to fit a standardized generalized hyperbolic distribution to my data. I am aware, that I can do this with the dsgh command of the fBasics package along with the optim command. My problem is, that I also want to have a derivation of it. So I need the theory behind it, i.e. I need the formula of the probability density function which they use a...

>>>>> Rodrigo Zepeda <rzepeda17 at gmail.com> >>>>> on Fri, 17 Mar 2017 12:56:06 -0600 writes: > Dear all, > We seem to have found a "strange" behaviour in the hyperbolic tangent > function tanh on Windows. > When running tanh(356 + 0i) the Windows result is NaN + 0.i while on Mac > the result is 1 + 0i. It doesn't seem to be a floating point error because > on Mac it is possible to run arbitrarily large numbers (say tanh( > 99...

Dear R People: There is a function from the fBasics library to get the probability and quantiles for the hyperbolic probability function. Is there one that will estimate parms of the hyperbolic probability function from a data set, please? Thanks in advance! Sincerely, Erin Hodgess mailto: hodgess at gator.uhd.edu R Version 2.0.1 windows

Dear all, We seem to have found a "strange" behaviour in the hyperbolic tangent function tanh on Windows. When running tanh(356 + 0i) the Windows result is NaN + 0.i while on Mac the result is 1 + 0i. It doesn't seem to be a floating point error because on Mac it is possible to run arbitrarily large numbers (say tanh( 99999967787364876751923819234812481234123418237...

I created a EM algorithm for Generalized hyperbolic distribution. I want to estimate mutheldaplus, sigmatheldaplus, betasigmaplus in my code. After getting use these value , then my iteration have to be begin of this code. But I can not to do iteration part. Can you help me use my code and get iteration ? Do know any useful code for EM algorithm...

For future reference: https://sourceforge.net/p/mingw-w64/mailman/message/35747206/ On Wed, Mar 22, 2017 at 2:12 PM, Jeroen Ooms <jeroenooms at gmail.com> wrote: > This looks like a bug in mingw-w64 CRT. The problem can be produced > with C++ without R: > > #include <iostream> > #include <cmath> > #include <complex> > > int main(){ >

I have got a data set that is Gross Primary Productivity ~ Total Suspended Solids it is a hyperbola just like: plot(1/c(1:1000)) how do I model this relationship so that I can get all of the neat things that lm gives residuals etc. etc. so that I can see if my eyeball model stands up. Thanks for any help, pointers, or good things to read. -- Stephen Sefick Research Scientist Southeastern

Dear all Currently, I'm implementing the generalized hyperbolic distribution into Splus. Unfortunately the Bessel function is not implemented in Splus. In R the Bessel function does exist but it is an internal function and I'm not able to look at the code. Is there any possibility to see the code of the Bessel function in R or does anybody has an implement...

Hi team, I am facing issues with PearsonIV distribution fitting in R. I am applying Hyperbolic and PearsonIV distributions on the equity returns in UK over a period of 30 years. For the same data set i am getting strikingly different results under which Hyperbolic distribution does produce negative percentiles of the return after fitting but PearsonIV distribution does not. I think there is...

On Tue, Jan 7, 2020 at 4:59 PM Doerfert, Johannes <jdoerfert at anl.gov> wrote: > Hi Bill, > > On 01/07, Bill Wendling via llvm-dev wrote: > > Then perhaps those opposed could suggest how to use Phabricator/Arcanist > so > > that I don't throw my keyboard through my monitor? > > Please explain your problems, w/o the hyperbole, so people can actually do >

...t(c(1:length(volatility)),volatility,type="l") #add VaR lines(quantile,type="l",col="red") So in this case I understand everything and I can implement this. But now comes my problem: I want to use a t-distribution with paramters mu, nu and beta or even a generalized hyperbolic distribution. So in this case, I don't know how to plug in the estimates for sigma, since there is no sigma in the paramters? How can I implement the volatility model and e.g. the generalized hyperbolic distribution in this case to calculate the Value at Risk? Thanks [[alternative HTML versi...

Then perhaps those opposed could suggest how to use Phabricator/Arcanist so that I don't throw my keyboard through my monitor? -bw On Tue, Jan 7, 2020 at 4:33 PM Finkel, Hal J. <hfinkel at anl.gov> wrote: > > On 1/7/20 6:17 PM, Bill Wendling wrote: > > What was the verdict? Any plans to move? I hate coding anything knowing > that I'll have to use Phabricator.

Dear R users, I'm trying to fit stable distribution and hyperbolic distribution to my data using stableFit(), and hypFit() of fBasics. However, there are some problems This is the result ====================================== > stableFit(lm, alpha = 1, beta = 0, gamma = 1, delta = 0, doplot = TRUE, trace = FALSE, title = NULL, description = NULL) Title: Stabl...

On Tue, Jan 7, 2020 at 5:35 PM Jonas Devlieghere <jonas at devlieghere.com> wrote: > On Tue, Jan 7, 2020 at 5:16 PM Bill Wendling via cfe-dev > <cfe-dev at lists.llvm.org> wrote: > > > > On Tue, Jan 7, 2020 at 4:59 PM Doerfert, Johannes <jdoerfert at anl.gov> > wrote: > >> > >> Hi Bill, > >> > >> On 01/07, Bill Wendling

> On Jan 7, 2020, at 17:35, Jonas Devlieghere via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > On Tue, Jan 7, 2020 at 5:16 PM Bill Wendling via cfe-dev > <cfe-dev at lists.llvm.org> wrote: >> >> On Tue, Jan 7, 2020 at 4:59 PM Doerfert, Johannes <jdoerfert at anl.gov> wrote: >>> >>> Hi Bill, >>> >>> On 01/07, Bill

...ility plot(c(1:length(volatility)),volatility,type="l") #add VaR lines(quantile,type="l",col="red") Now, I want to change the volatility model to a more advanced model (EWMA, ARCH, GARCH) and the distribution to a more sophisticated distribution (student, generalized hyperbolic distribution). My main question is now, how can I combine the volatility model and the distribution, since in case e.g. of a Student's-t distribution with parameters mu (location), v (df), beta (scale) I cannot just plug the sigma in, because the distribution has no sigma? One solution I alrea...

...on of “poison” has ever been discussed before, you were will intentioned in saying it has, but there is no reason to believe it has, because every time I dig deeper into these issues I run into mis-conceptions and mis-information. Faulty analysis based on faulty assumptions. Every time. If I sound hyperbolic it is because I have gotten frustrated from continually running into this. And before you claim that I have insulted Dan, you might want to get his opinion on the subject. My bet is he will react by saying “why didn’t I think of that”, but in spite of my trying to contact him I have gotten no res...

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,...