similar to: How to standardize the generalized hyperbolic distribution?

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 and the derivation of it. I thought about

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) {

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 help mailing list archive at Nabble.com.

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: Stable Parameter Estimation

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

>>>>> 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

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

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(

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

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 an

Hi, I am trying to calculate probability density of normal inverse gaussian distribution. I am using dnig function of fBasics package. However, I am getting following result. The density at x = 0.003042866 is: > dnig(x= 0.003042866, alpha=5.184868, beta= 0.11841, delta= 0.06038513, mu= -0.0003520626) [1] 6.550251 I am not sure why it is 6.550251. Can anyone tell me why density is more than

Hello, I am a new user of R. I am trying to use the packages fBasics and fExtremes when i am running the examples I get few error. Could someone tell me what is happenig? Thank you beforehand. from Fbasics packages: xmpfBasics() Error in file(file, "r") : unable to open connection In addition: Warning message: cannot open file '/usr/lib/R/library/fBasics/demoIndex'

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 Generalized Hyperbolic library(QRMlib)

It is a pleasure for me to announce the new built for Rmetrics Version 191.0057. The source files and Windows binary packages can be downloaded from www.rmetrics.org . The new built has also been submitted to the CRAN server. Some new functions and example files have been added. Unfortunately the user guides and reference guides are not yet updated, they have still the status of Version

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(){ >

Can anyone explain such different output: > stableFit(s,alpha = 1.75, beta = 0, gamma = 1, delta = 0, + type = c("q", "mle"), doplot = TRUE, trace = FALSE, title = NULL, + description = NULL) Title: Stable Parameter Estimation Call: .qStableFit(x = x, doplot = doplot, title = title, description = description) Model: Student-t Distribution Estimated

When I try to load "fBasics" package, I get following error/warning : > library(fBasics) Loading required package: fImport Loading required package: fSeries Loading required package: fBasics Loading required package: fImport Loading required package: fSeries Loading required package: fBasics Loading required package: fImport Loading required package: fSeries Loading required package:

Hi, I am having trouble using constrOptim. My target is to do a portfolio optimization and there some constraints have to be fulfilled. 1) The weight of each share of the portfolio has to be greater than 0 2) The sum of these weights has to be 1 I am able to fulfill either the first or the second constraint but not both. One simple way would be to fulfill the first constraint by using optim as

I'm using stableFit from the package fBasics to estimate the parameters of a truncated normal distribution (I'm interested in the parameters of the underlying normal distribution). It is correct to generalize this truncated normal distribution as a stable distribution ? Thanks David -- View this message in context:

Hi all, I am trying to fit t distribution using the function "tFit" in the library(fBasics). I am using the code tFit(datac[[2]]) and it returns the following list. Title: Student-t Parameter Estimation Call: tFit(x = datac[[2]]) Model: Student-t Distribution Estimated Parameter(s): df 78.4428 I just wonder how can I refer to the estimated parameters. I tried