search for: arma

...9;t find any trace of my previous attempt in the archive.) I'm having trouble with forecast() in the dse2 package. It works fine for me on a model without a trend, but gives me NaN output for the forecast values when using a model with a trend. An example: # Set inputs and outputs for the ARMA model fit and test periods arma.fit.input <- c(105.3332, 105.3573, 105.3113, 105.1493, 105.1209, 105.2111, 104.9161, 105.3654, 105.4682, 105.6789, 105.6297, 106.0155, 105.8454, 105.4322, 105.6062, 106.0739, 106.1109, 105.4470, 104.9739, 105.3427, 105.4305,...

Thanks a lot to everybody that helped me out with this. Conclusions: (1) In order to edit arima in R: >fix(arima) or alternatively: >arima<-edit(arima) (2) This is not contained in the "Introduction to R" manual. (3) A "productive" fix of arima is attached (arma coefficients printed out and error catched so that it doesn't halt parent loops to search for candidate coefficients): Note 1: "productive" means I'm a beginner in R so there is probably a better way to print the error message and fill the output arguments (I only return NA in aic...

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 Sk...

Dear all, running the example by D. Eddebuettel (http://dirk.eddelbuettel.com/blog/2011/04/23/) I get an error message. Specifically, the R code I was taking from the above example is ### BEGIN EXAMPLE ### suppressMessages(require(RcppArmadillo)) suppressMessages(require(Rcpp)) suppressMessages(require(inline)) code <- ' arma::mat coeff = Rcpp::as<arma::mat>(a); arma::mat errors = Rcpp::as<arma::mat>(e); int m = errors.n_rows; int n = errors.n_cols; arma::mat simdata(m,n); simdata.row(0) = arma::zero...

...nthlyBLA,mcReg) LinearModel1.res <- residuals(linearModel1) LinearModel2.res <- residuals(linearModel2) LinearModel3.res <- residuals(linearModel3) LinearModel4.res <- residuals(linearModel4) LinearModel5.res <- residuals(linearModel5) #hmmm bolt on linearModel[x] as linearModel[x]$arma.fit? arma1.fit <- auto.arima(LinearModel1.res) arma2.fit <- auto.arima(LinearModel2.res) arma3.fit <- auto.arima(LinearModel3.res) arma4.fit <- auto.arima(LinearModel4.res) arma5.fit <- auto.arima(LinearModel5.res,stepwise=T,trace=T) #Ok what is left over after Regression and ARIMA...

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...

...#39;dse1' The following object(s) are masked from package:stats : acf simulate > library("dse2") > > AR <- array(c(1, 0.5, 0.3, 0, 0.2, 0.1, 0, 0.2, 0.05, 1, 0.5, 0.3), c(3, 2, + 2)) > MA <- array(c(1, 0.2, 0, 0.1, 0, 0, 1, 0.3), c(2, 2, 2)) > arma <- ARMA(A = AR, B = MA, C = NULL) > data.arma.sim <- simulate(arma) > > data.arma.sim output data: Error: evaluation nested too deeply: infinite recursion / options(expressions=)? > ############################################################# ###############################...

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...

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...

...) on this: library(tseries) garch(r) The estimated parameters are given below: ***** ESTIMATION WITH ANALYTICAL GRADIENT ***** Call: garch(x = r) Coefficient(s): a0 a1 b1 4.746e-06 6.837e-02 8.877e-01 Now it is straightforward to transform Garch(1,1) to a ARMA like this: r[t]^2 = w + (alpha+beta)*r[t-1]^2 + beta*(h[t-1] - r[t-1]^2) - (h[t] - r[t]^2) = w + (alpha+beta)*r[t-1]^2 + beta*theta[t-1] + theta[t] So if I fit a ARMA(1,1) on r[t]^2 I am getting following result; arma(r^2, order=c(1,1)) Call: arma(x = r^2, order = c(1, 1)) Coeffic...

In the summary of the output of arma, there's a number Pr(>|t|), however, I don't know what is its meaning - at least, it doesn't _seem_ to be a Student's t distribution. Reproducible test case: x <- c(0.5, sin(1:9)) reg <- arma(x, c(1,0)) summary(reg) <output> Call: arma(x = x, order = c(1, 0)...

Hello, I am running an ARMA model to run forecast for changes in S&P 500 prices. My ARMA calculations look as follows armacal <- arma( spdata, order = c(0,4), lag = list(ma = c(1,2,4)) ) Output: Call: arma(x = spdata, order = c(0, 4), lag = list(ma = c(1, 2, 4)) ) Coefficient(s): ma1 ma2 ma4 i...

Dear Sir, I think I found a bug in the function arma.sim, which is defined in the help page of the function filter: arma.sim <- function(n, ar = NULL, ma = NULL, sigma = 1.0) { x <- ts(rnorm(n+100, 0, sigma^2), start = -99) if(length(ma)) x <- filter(x, ma, sides=1) if(length(ar)) x <- filter(x, ar, method="recursive&quo...

Dear R experts, I am trying to estimate an ARMA 2,2 model with garch errors. I used the following code on R 2.9. #library library(fGarch) #data data1<-ts(read.table("C:/Users/falcon/Desktop/Time Series/exports/goods1.csv"), start=c(1992,1), frequency=12) head(data1) #garch garchFit(formula.mean= ~arma(2,2),formula.var=~garch(1,1),...

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]]

Hi all, I am fitting an ARMA(1,(1,4)) model. y(t) = a*y(t-1) + e(t) + b1*e(t-1) + b4*e(t-4) > arma1.14 <- arma(series, lag=list(ar=1, ma=c(1,4)), + include.intercept = F, qr.tol = 1e-07) works fine: Coefficient(s): ar1 ma1 ma4 0.872 -0.445 0.331 I want to forecast 50 periods....

Dear List, I am new to TS-Modeling in R. I would like to fit an ARMA(1,1) model for a balanced panel, running Y on a full set of unit and year dummies using an arma(1,1) for the disturbance: y_it=unit.dummies+yeardummies+e_it where: e_it=d*e_it-1+u_it+q*u_it-1 How can I fit this model in R? arma() does not seem to take covariates (or I don't understand how to...

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=lis...

Hi, I want to fit a regression model with one independent variable. The error part should be fitted an ARMA process. For example, y_t = a + b*x_t + e_t where e_t is modelled as an ARMA process. Please let me know how do I do this in R. What code should I use? TIA Aditya [[alternative HTML version deleted]]

Hello Following some standard textbooks on ARMA(1,1)-GARCH(1,1) (e.g. Ruey Tsay's Analysis of Financial Time Series), I try to write an R program to estimate the key parameters of an ARMA(1,1)-GARCH(1,1) model for Intel's stock returns. For some random reason, I cannot decipher what is wrong with my R program. The R package fGarch alread...