similar to: fGarch - Fitting and APARCH-Modell with fixed delta

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 well, but I need other characteristics of

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-to-convert-string-to-object-tp2999281p2999281.html Sent from the R help mailing

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

Dear expeRts, How can I specify the order p,q of a GARCH(p,q) model within a loop? Here's a minimal example showing that an "Formula and data units do not match"-error appears: library(fGarch) spec <- garchSpec(model = list(alpha = 0.1, beta = c(0.4, 0.4))) data <- garchSim(spec, n = 100) x <- list() for(q in 1:3){ print(q) x[q] <-

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") No help files found with alias or concept or

I use fGarch package to estimate AR(1)-ARCH(1) process for a vector of returns. Then, using the estimated parameters I want to simulate 10 000 sample paths where each path has the same length as the vector of returns. So the first line of the code is: spec=garchSpec(model=list(ar= 0.440270860, omega=0.000374365,alpha=0.475446583 , mu=0, beta=0))---- The only way I can think of generating 10 000

Hi folks! After updating my packages my R seems to have completely crashed as will not start up - even after I installed 2.8.1 from 2.8.0. I get the following: Fatal error: unable to restore saved data in .Rdata Error in loadNamespeace(name): there is no package called fGarch But I do have a package called fGarch. After I hit ok, it crashes and exits. I cannot use any functionality at all.

Hello. I am using fGarch to estimate the following model: Call: garchFit(formula = fmla, data = X[, i], trace = F) Mean and Variance Equation: data ~ arma(1, 1) + garch(1, 1) Conditional Distribution: norm Coefficient(s): mu ar1 ma1 omega alpha1 beta1 -0.94934 1.00000 -0.23211 54.06402 0.45709 0.61738 Std. Errors: based on Hessian Error Analysis:

Hello, I was using garchFit {fGarch} to fit some GARCH processes. I noticed that the result contains "Log Likelihood" value (right above "Description"), but when I use .. at fit$llh to retrieve Log Likelihood value, the sign switched. I am confused about which value I should choose to report... Any help here? Thanks a lot! Ted -- View this message in context:

Greetings, Suppose I fit an fGarch model via garchFit function for a time series X. I'm wondering is there any easy way to apply the fitted model to a different time series Y to calculate conditional variances and standardized residuals? Thanks. -- View this message in context: http://r.789695.n4.nabble.com/Applying-previously-fitted-fGarch-model-tp3249585p3249585.html Sent from the R help

Dear all- Package /fGarch/ version 2100.78 in R version 2.8.1 (2008-12-22) running on linux 2.6.22.9-91.fc7 In trying to fit garch models in above environment. I am getting "reasonable" fitted coefficients, but the fitObject@fitted are all the same. This is true even for the help page example: library(fGarch) R> X.timeSeries = as.timeSeries(msft.dat) R> head( +

Hello, The function garchFit in the package fGarch allows for choosing a conditional distribution, one of which is the t-distribution. The function allows specification of the shape parameter of the distribution (equal to the degrees of freedom for the t-distribution), for which the default is set to 4. The function also includes an option "include.shape", which is "a logical flag

Good day everyone, I fitted a GARCH model to a time series and R estimated the model and provide me with the estimates. However, when I tried to extract the fitted values from the estimated model I got the following error message: "Error in .local(object, ...) : object "fit" not found"   I used the following to extract the fitted values fitted_TASI <- fitted(garchFit(~

hello everybody, I would like to fit a model to a times series (testing set) for out of sample predictions using garchFit(). I would like to keep the coefficients of ARMA/GARCH model fixed (as found by fitting the model to my training set). The arima fitting function has such an option for that (fixed=NULL) but the garchFit() doesnt. It is very important for me to keep the same coefficients

Hi, i am working in the forecast of the daily price crude . The last prices of this data are the following: 100.60 101.47 100.20 100.06 98.68 101.28 101.05 102.13 101.70 98.27 101.00 100.50 100.03 102.23 102.68 103.32 102.67 102.23 102.14 101.25 101.11 99.90 98.53 96.76 96.12 96.54 96.30 95.92 95.92 93.45 93.71 96.42 93.99 93.76 95.24 95.63 95.95 95.83 95.65

Hello I am trying to use predict from an arma-Garch model (arma(2, 2) + garch(1, 1)) and I am getting the following error: Error en arima(x = object@data, order = c(max(u, 1), 0, max(v, 1)), init = c(ar, : non-stationary AR part from CSS Does anybody know what can be the reason of this error? The model I have estimated is the following: Title: GARCH Modelling Call: garchFit(formula =

Hi, I am attempting to fit a ARMA/GARCH regression model without success. ### ARIMA-GARCH model with regressor ### ### Time series data: A multivariate data set. cov.ts.dq = cov.ts[1:4,"dq1"][!is.na(cov.ts[,"dq1"])] cov.ts.day = ts.intersect(dq = diff(q.ts), day = lag(q.ts, -1)) ### The following R scripts work: (summary(no.day.fitr <- garchFit(dq ~ arma(0,3) +

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

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

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 <-