similar to: fractional cointegration

Dear list, Can one suggest me if there is an R function/package to estimate and simulate vector autoregressive (VAR) model allowing for the GARCH effect please? Thanks Mamush [[alternative HTML version deleted]]

Dear users, I am preparing a presentation in latex(beamer) . I would like to show parts of my plots per click. Example, consider I have two time series x and y: x<-ts(rnorm(100), start=1900,end=1999) y<-ts(rnorm(100), start=1900,end=1999) plot(x) lines(y,col=2) Then I imported this plot into latex as ".eps" file. My question is, how can i show plot of each time series separately

Dear members, I estimated a vector error correction model (VECM) using the "ca.jo" function in package "urca". I need to simulate the estimated model using R. I am aware how to simulate a VAR(p) model. Since the VECM is in difference form, I can't modify the VAR simulation codes to VECM. May one help me in this regard please? Thanks Mamush [[alternative HTML version

Hello, I am using urca package to run cointegration. I would like to find the standard error in the (normalized, Johansen) cointegration relationship. How can I do it? As far as I know, The function "cajorls" in the "urca" package provides the normalized cointegrating relationships. Nevertheless, it does not provide the standard deviation of the coefficient for each

Dear all, S+Finmetrics has a number of very specilised functions. I am particularly interested in the estimation of cointegrated VARs (chapter 12 of Zivot and Wang). In this context the functions coint() and VECM() stand out. I looked at package "dse1", but found no comparable functionality. Are there any other packages you could point me to? In general, are there efforts for

Hello, does anyone know about: a) simulating seasonal ARIMA models? arima out of package ts can fit it, but it does not look like it can simulates data from seasonal models b) fitting and simulating fractional seasonal ARIMA models? Hints will be appreciated, Henning -- Henning Rust Potsdam Institute for Climate Impact Research Dept. Integrated Systems Analysis Tel.: #49/331/288-2596

Hi all, Can I run a cointegrating regression, for example delta Xt=a1(Yt-1-cXt-1)+E1t and delta Yt=-b1(Yt-1-cXt-1)+E2t with R were Xt and Yt are non stationary time series at t a,b,c are parameters and E1t and E2t are error terms at t. Yt-Xt is stationary Any suggestions are welcome. Best regards, /fb -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing

Dear list and Martin, I'm testing different approaches to fit an electricity demand time series and come upon the fracdiff package (v 1.3-1) for fitting fractional ARIMA models. The following questions are motivated by this package. 1. Despite having a help page, the residuals and fitted functions don't seem to have implementation, or did i miss something obvious? Alternatively, having a

Full_Name: Jussi Mäkinen Version: 1.6.2 OS: Win2000 Submission from: (NULL) (193.210.145.2) I tried to download fracdiff from http://www.stat.unipg.it/stat/statlib/R/CRAN/ but I got the messages box: The procedure entry point daxpy_ could not be located in the dynamic link library R.dll and the following lines to RGui: Error in dyn.load(x, as.logical(local), as.logical(now)) : unable

Hi, I'm using the function fracdiff and can not figure out how to get the estimated values for sigma2 or confidence intervals for the parameter estimates. Does anyone know how to obtain these values? Thanks, Melissa

Hello, I want to know if there are some functions or packages to solve differential and integral equation using R. Thanks. Shao chunxuan. [[alternative HTML version deleted]]

I was sniffing in the fracdiff library (this is for fractionally integrated ARMA processes; Haslett and Raftery 1989). The documentation suggests that one tries the following simple example: library(fracdiff) ts.test <- fracdiff.sim( 5000, ar = .2, ma = -.4, d = .3) fracdiff( ts.test$series, nar = length(ts.test$ar), nma = length(ts.test$ma)) When I run this, I get the following error: R

Hello! I'm using the blrtest() function in the urca package to test cointegration relationships. Unfortunately, the hypothesis (restrictions on beta) specifies the same restriction on all cointegration vectors. Is there any possibility to specify different restrictions on the cointegration vectors? Are there any other packages in R using cointegration tests? Thanks and best regards. Dennis

Hi - i am looking for a package with which I can perform panel cointegration tests. Old threads suggest plm and urca package, but I don't find suitable tests in these packs. Somebody knows more? best regards, Philipp -- View this message in context: http://r.789695.n4.nabble.com/panel-cointegration-tp4593443p4593443.html Sent from the R help mailing list archive at Nabble.com.

Dear R Core Team, I am using package {urca} to do cointegration and estimate ECM model, but I have the following two problems: (1) I use ca.jo() to do cointegration first and can get the cointegration rank, alpha and beta. The next step is to test some restrictions on beta with blrtest(),bh5lrtest(), and bh6lrtest(). But none of them can add restrictions on all the cointegration

Hi, I am trying to test the cointegration among 5 time series, grouped in pairs. I would like to save in a table the cointegration vectors for the 10 tests. I used the urca package, but I dont know how to extract the data only for the cointegration vector. Thanks in advance for help ! Eduardo

Hi, Could someone please tell me the R codes for fitting VAR(p) (Vector Auto Regressive) models and doing the Johansen?s cointegration tests. TIA Aditya

Dear All, I am looking for a cointegration relationship between Spot and Future Price of commodites. The problem i am facing follows: 1. After estimating by Engle-Grranger Method, i found that the residuals are stationary at their level I (o), which is required to fulfill the cointegration test. But the autocorrelation problem arises, as DW statistics is signficantly low 0.50-0.88 for various

Hi, I am trying to estimate a VECM without constant using the following code: data(finland) sjf <- finland sjf.reg<-ca.jo(sjf, type = c("eigen"), ecdet = c("none"), K = 2,spec=c("transitory"), season = NULL, dumvar = NULL) cajools(sjf.reg) While the cointegration test does not use a constant, it is used in the cajools which I do not want. I am sure I am

Hello, I tried to use urca package (R) for cointegration analysis. The data matrix to be investigated for cointegration contains 8 columns (variables). Both procedures, Phillips & Ouliaris test and Johansen's procedures give errors ("error in evaluating the argument 'object' in selecting a method for function 'summary'" respectiv "too many variables,