similar to: ARMA and AR in R

Hello, The "arma" function in the "tseries" package allows estimation of models with specific "ar" and "ma" lags with its "lag" argument. For example: y[t] = a[0] + a[1]y[t-3] +b[1]e[t-2] + e[t] can be estimated with the following specification : arma(y, lag=list(ar=3,ma=2)). Is this possible with the "arima" function in the

Hi, i am learning R recently and find it very helpful in time series model. In ARMA model, given (p,q) it can get the estimation of a[i] and b[j] easily with arima() function. X[t] = a[1]X[t-1] + ... + a[p]X[t-p] + e[t] + b[1]e[t-1] + ... + b[q]e[t-q] but in my recent data model, i met a problem. In the ARMA model, p and q are fixed, but there are some constraints in the parameters

> It might clarify your thinking to note that a seasonal ARIMA model > is just an ``ordinary'' ARIMA model with some coefficients > constrained to be 0 in an efficient way. E.g. a seasonal AR(1) s = > 4 model is the same as an ordinary (nonseasonal) AR(4) model with > coefficients theta_1, theta_2, and theta_3 constrained to be 0. You > can get the same answer as from

Hi given an ARMA process and the AR and MA coefficients I need the residuals. arima() calculates the residuals together with the best AR and MA coefficients, but I need the coefficients to take known values. In S-PLUS there is a function arima.filt(). Is there something similar in R? Thanks for any help, Matthias Budinger

Hi R-Community, so far I dealt with univariate processes and used the function "arima" to estimate an ARMA(1,1)-model. For multivariate processes there are the functions "estVARXar" and "estVARXls" from package "DSE". But how can I estimate an VARMA(1,1)-model, or even better determine the orders and estimate the parameters? Much thanks in advance, Hagen

Hi, I'm trying to model an ARMA(1,[1,4]), i.e. I want only lags 1 and 4 of the Moving Average part. It's the '[1,4]' part that is giving me a problem. I've tried different arma's and arima's in different packages, namely: packages tseries, fArma, FinTS, timeSeries, TSA, Zelig, ds1, forecast For example, with package FinTS: > ( ARIMA(y, order=c(1,0,c(1,4))) )

Hi, I am new to using R for Time series analysis. I was wondering if there are any functions that can convert ARMA or ARIMA time series into their corresponding AR or MA time series representations (by calculating the corresponding AR or MA coefficients). Thanks a lot Kris.

Another pathological test. arima does not crash for that series that crashes arma: arima(c(2.01, 2.22, 2.09, 2.17, 2.42), order=c(1,0,0)) However, arima crashes for this: arima(c(1.71, 1.78, 1.95, 1.59, 2.13), order=c(1,0,0)) arima seems pretty consistent in its crashing behaviour, since crashing for one series means crashing for all affine series: lets.crash.arima <- c(71, 78, 95, 59,

Dear R People: I have the following situation. I have observations that are 128 samples per second, which is fine. I want to fit them with ARIMA models, also fine. My question is, please: when I do my forecasting, do I need to do anything special to the "n.ahead" parm, please? Here is the initial setup: > xx <- ts(rnorm(128),start=0,freq=128) > str(xx) Time-Series

Hello,Could somebody tell me what is the difference between  theese 3 calls of functionsarma(x,order=c(1,0)), arima(x,order=c(1,0,0)) ar(x,order=1)?I expected same residuals of theese three models,but unexpectably for the first two R requiredinitial value of something (what?)...Thanks in advance!  [[alternative HTML version deleted]]

When I do ARMA(2,2) using one lag of LCPIH data This is eview result > > *Dependent Variable: DLCPIH > **Method: Least Squares > **Date: 08/12/11 Time: 12:44 > **Sample (adjusted): 1970Q2 2010Q2 > **Included observations: 161 after adjustments > **Convergence achieved after 14 iterations > **MA Backcast: 1969Q4 1970Q1 > ** > **Variable Coefficient Std.

Dear list members, I am trying to estimate parameters of the AR(1)-GARCH(1,1) model. I have one additional dummy variable for the AR(1) part. First I wanted to do it using garchFit function (everything would be then estimated in one step) however in the fGarch library I didn't find a way to include an additional variable. That would be the formula but, as said, I think it is impossible to add

Hello - Here's what I'm trying to do. I want to fit a time series y with ARMA(1,1) + GARCH(1,1), there are also an exogeneous variable x which I wish to include, so the whole equation looks like: y_t - \phi y_{t-1} = \sigma_t \epsilon_t + \theta \sigma_{t-1} \epsilon_{t-1} + c x_t where \epsilon_t are i.i.d. random variables \sigma_t^2 = omega + \alpha \sigma_{t-1}^2 + \beta

Hello, BODY { font-family:Arial, Helvetica, sans-serif;font-size:12px; } Does any one know if there are any functions/packages available in R for robust fitting of ARMA time series models (e.g., similar to the function arima.rob() in S-PLUS)? Many thanks and kind regards, Isabella Isabella R. Ghement, Ph.D. Ghement Statistical Consulting Company 301-7031 Blundell Road,

Dear R-helpers, I would appreicate if someone can help me on the transfer parameter in ARIMAX and also see what I am doing is correct. I am using ARIMAX with 2 Exogeneous Variables and 10 years data are as follows: DepVar Period, depVar, IndepVar1 Period, indepVar1, IndepVar2 Period, indepVar2 Jan 1998,708,Jan 1998,495,Jan 1998,245.490 Feb 1998,670,Feb 1998,421.25,Feb 1998,288.170 Mar

I'd like to fit an ARMA(1,1) model to some data (Federal Reserve Bank interest rates) that looks like: ... 30JUN2006, 5.05 03JUL2006, 5.25 04JUL2006, N &lt;---- here! 05JUL2006, 5.25 ... One problem is that holidays have that "N" for their data. As a test, I tried fitting ARMA(1,1) with and without the holidays deleted. In other words, I fit the above data

Why the standadard errors of the coefficientes of the arma models fited by using the arima procedure in the stats package doesnt coincide with that of S+, minitab or SAS? -- Este mensaje ha sido analizado por MailScanner en busca de virus y otros contenidos peligrosos, y se considera que est? limpio.

Dear R users, I need to fit an ARMA model. As far as I've seen, EACF (extended ACF) is not available in R. 1. Let's say I fit a series of ARMA models in a loop. Given the code/output included below, how do I pull 'Model' and 'Fit' (AIC) from each summary() so that I can combine them into an array/data frame to be sorted by AIC? 2. Apart from EACF, are you aware perhaps

Hi there, Does anyone know how to predict ARMA? It doesn?t have either predict or forecast methods. I found couple of packages called fbasic and fseries at http://www.itp.phys.ethz.ch/econophysics/R/, which has ?arma.predict? in it, but it doesn?t seem to be working. Any help in this regard would be appreciated. Thanks in advance. Regards Skanda Kallur "Prediction is very difficult,

Hello, I try to simulate an ARMA-model using R, but I didn't find any function to generate such timeseries. In Splus there is the function arima.sim which generates AR-, MA- and ARIMA-series. Is there any similar in R? Best regards, Frank Beimfohr -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read