search for: aparch

Hi, Could somebody say if it is possible to compute APARCH-models with garchFit commands. I have earlier used aaa (garchOxFit) and now I try to use bbb (look below) aaa <- garchOxFit(formula.mean=~arma(1,0),formula.var=~aparch(1,1),series=nyk,cond.dist=c('gaussian')) bbb <- garchFit(formula=~arma(1,0)+aparch(1,1),data=nyk) aaa works w...

Hi there, I'm trying to fit a GJR-GARCH Model using fGarch. I wanted to try that by fitting an APARCH model with a fixed delta of 2 and a non-fixed gamma. So I was simply trying to use: spec <- garchFit(~aparch(1,1),data=garchSim(),delta=2) coef(spec) And sometimes, it's working like a charm and delta is indeed exactly 2 in the resulting coefficient vector. Frequently, though, the resultin...

temp = "~aparch(" temp1 = paste(temp,1, sep = "") temp2 = paste(temp1,1, sep = ",") temp3 = paste(temp2, ")",sep = "") temp 3 is a character but I want to convert to formula object. How do I do this? -- View this message in context: http://r.789695.n4.nabble.com/how-t...

Dear R people, I'm not able to have the component residuals, fitted.value ....from an aparchFit() estimation as explain in the Value of aparchFit Help, package fSeries. Could someone help me? Thanks in advance. Lisa

Dear R-helper, I wish to implement the APARCH model as described in the fSeries documentation. But I get the following: >library(fSeries) [...] > ?aparchFit No documentation for 'aparchFit' in specified packages and libraries: you could try 'help.search("aparchFit")' > help.search("aparchFit&quot...

If I have a model line = lm(y~x1) and I want to use a for loop to change the number of explanatory variables, how would I do this? So for example I want to store the model objects in a list. model1 = lm(y~x1) model2 = lm(y~x1+x2) model3 = lm(y~x1+x2+x3) model4 = lm(y~x1+x2+x3+x4) model5 = lm(y~x1+x2+x3+x4+x5)... model10. model_function = function(x){ for(i in 1:x) { } If x =1, then the list

Dear R-Users, I'm searching for somebody who can support me or even likes to collaborate with me in setting up an R-package for "constrained maximim log-likelihood" parameter estimation. For example fitting the parameters of a MA(1)-APARCH(1,1) model for a time series of 17'000 points (e.g. the famous Ding-Granger-Engle mode) takes about 10 minutes with the existing optimization algorithms available under R. Modern state of the art algorithms, like SQP algorithms as implemented in Gauss, Matlab, Ox, take about a few seconds....

Dear List, I'm now using Ubuntu 10.10 and I want to use the garchoxfit function.It seems that I need to download the package. While after installing the package,I still can't use the garchoxfit function.What's the reason and how to fix that? Thanks for your time! Best, Ning

Hello R-list-members, I'm trying to model ARMA(0,2) & GARCH(1,1) process using the code below, but according to my textbook, the estimated parameters are wrong. The MA-parameters should be negative. (I've got the same problem using garchFit()). Can anyone tell me what I'm doing wrong? And how can I calculate the hessian matrix? Many thanks, Desislava Kavrakova Code:

Hi, Although my doubt is pretty,as i m not from stats background i am not sure how to proceed on this. Currently i am doing a forecasting.I used ARIMA to forecast and time series was volatile i used garchFit for residuals. How to use the output of Garch to correct the forecasted values from ARIMA. Here is my code: ###delta is the data fit<-arima(delta,order=c(2,,0,1)) fit.res <-