similar to: Observation error in arima

HI, there, When i use R, i tried to use function arima(), it complains: Error: couldn't find function "arima" But when I type "help.search("arima") ", I got arima() poped up.. arima(ts) ARIMA Modelling of Time Series arima.sim(ts) Simulate from an ARIMA Model arima0(ts) ARIMA Modelling of Time Series -- Preliminary

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,

Hi, I have the following code from Splus that I'd like to migrate to R. So far, the only problem is the arima.filt function. This function allows me to filter an existing time-series through a previously estimated arima model, and obtain the residuals for further use. Here's the Splus code: # x is the estimation time series, new.infl is a timeseries that contains new information # a.mle

I am using arima to develop a time series regression model, I am using arima b/c I have autocorrelated errors. Several of my independent variables are categorical and I have coded them as factors . When I run ARIMA I don't get any warning or error message, but I do not seem to get estimates for all the levels of the factor. Can/how does ARIMA handle factors in xreg? here is some example

Hello R users, Hope everyone is doing great. I have a dataset that is in .csv format and consists of two columns: one named Period (which contains dates in the format yyyy_mm) and goes from 1995_10 to 2007_09 and the second column named pcumsdry which is a volumetric measure and has been formatted as numeric without any commas or decimals. I imported the dataset as pauldataset and made use of

As I am reading ?arima, only NA entries in the argument fixed= imports. The following seems to indicate otherwise: x <- arima.sim(model=list(ar=0.8), n=100) + (1:100)/50 > t <- 1:100 > mod1 <- lm(x ~ t) > > init1 <- c(0, coef(mod1)[2]) > fixed1 <- c(as.numeric(NA), 0) > > arima(x, order=c(1,0,0), xreg=t, include.mean=FALSE, init=init1, fixed=fixed1)

Dear List, A posting to R-Help exposed this problem with the print method for objects of class Arima: > set.seed(1) > x <- arima.sim(n = 100, list(ar = 0.8897, ma = -0.2279)) > mod <- arima(x, order = c(1,0,1)) > coefs <- coef(mod) > mod2 <- arima(x, order = c(1,0,1), fixed = coefs) > mod2 Call: arima(x = x, order = c(1, 0, 1), fixed = coefs) Coefficients: Error

Hi, I am trying to forecast a model using predict.Arima I found arima model for a data set: x={x1,x2,x3,...,x(t)} arima_model = arima(x,order=c(1,0,1)) I am forecasting the next N lags using predict: arima_pred = predict(arima_model,n.ahead = N, se.fit=T) If I have one more point in my series, let's say x(t+1). I do not want to recalibrate themodel, I just want to forecast the next N-1

I have been trying to simulate from a time series with trend but I don't see how to include the trend in the arima.sim() call. The following code illustrates the problem: # Begin demonstration program x <- c(0.168766559, 0.186874000, 0.156710548, 0.151809531, 0.144638812, 0.142106888, 0.140961714, 0.134054659, 0.138722419, 0.134037018, 0.122829846, 0.120188714,

Dear R People: Here is some output from AR and ARIMA functions: > xb <- arima.sim(n=120,model=list(ar=0.85)) > xb.ar <- ar(xb) > xb.ar Call: ar(x = xb) Coefficients: 1 0.6642 Order selected 1 sigma^2 estimated as 1.094 > xb.arima <- arima(xb,order=c(1,0,0),include.mean=FALSE) > xb.arima Call: arima(x = xb, order = c(1, 0, 0), include.mean = FALSE)

Hi, I am trying to understand exactly what xreg does in arima. The documentation for xreg says:"xreg Optionally, a vector or matrix of external regressors, which must have the same number of rows as x." What does this mean with regard to the action of xreg in arima? Apparently somehow xreg made the following two arima fit equivalent in R: arima(x, order=c(1,1,1), xreg=1:length(x)) is

I'm playing with predict.Arima in the 3/19/02 development snapshot of R-devel. The following produces an error message because x is not of class "ts": R> x <- rnorm(20) R> obj <- arima(x, c(2,0,0)) R> predict(obj) Error in round(x, digits) : Non-numeric argument to mathematical function Granted the documentation for arima says x should be a time-series, but

In some time series simulations I'm doing, I occasionally want the model to be ``white noise'', i.e. no model at all. I thought it would be nice if I could fit this into the arima.sim() context, without making an exceptional case. I.e. one ***could*** do something to the effect if(length(model)==0) x <- rnorm(n) else x <- arima.sim(model,n) but it would be more suave if one

Dear sirs, I would like to know if there is a function to compute the pvalue for the significancy of arima coef in an arima object created by the arima function. I have written this one: pvalueArima<-function(x,arima) { t<-(arima$coef)/(diag(arima$var.coef)^0.5) df<-length(x)-length(arima$coef) 1-pt(t,df) } Has somebody already implemented something equivalent ? thank you for your

Dear all, how can I use vcovHC() to get robust/corrected standard errors from an arima() output? I ran an arima model with AR(1) and got the estimate, se, zvalue and p-value using coeftest(arima.output). However, I cannot use vcovHC(arima.output) to get corrected standard errors. It seems vcovHC works only with lm and plm objects? Is there another way I can get robust/corrected

Hi, All, This is my program ts1.sim <- arima.sim(list(order = c(1,1,0), ar = c(0.7)), n = 200) ts2.sim <- arima.sim(list(order = c(1,1,0), ar = c(0.5)), n = 200) tdata<-ts(c(ts1.sim[-1],ts2.sim[-1])) tre<-c(rep(0,200),rep(1,200)) gender<-rbinom(400,1,.5) x<-matrix(0,2,400) x[1,]<-tre x[2,]<-gender fit <- arima(tdata, c(1, 1, 0), method = "CSS",xreg=t(x))

Hey, as a bloddy beginner in R I want to simulate a Arima (2,1,0) process with R. My problem is, that I don't know how to specify the AR. For a ARIMA(1,1,0) I use the following syntax: S <- arima.sim(list(order=c(1,1,0), ar=0.9), n=100). I think it is a stupid question with an easy answer. But when I google the only results are arima.sim for an ARIMA (1,1,0). Regards, Chris --

Good morning everyone, I have attached an Excel file that contains a macro from which I call and use R's auto.arima function to generate forecasts. The program runs perfectly and it gets me the results; however, those results are pretty unusual. I also tried using the auto.arima function directly in the R console and still get weird results. The results are shown in columns AB, AC and AD

Hi, Can anyone explain how the standard error in arima() is calculated? Also, how can I extract it from the Arima object? I don't see it in there. > x <- rnorm(1000) > a <- arima(x, order = c(4, 0, 0)) > a Call: arima(x = x, order = c(4, 0, 0)) Coefficients: ar1 ar2 ar3 ar4 intercept -0.0451 0.0448 0.0139 -0.0688 0.0010 s.e.

Hello, I have used the arima.sim function to generate a lot of time series, but to day I got som results that I didn't quite understand. Generating two time series z0 and z1 as eps <- rnorm(n, sd=0.03) z0 <- arima.sim(list(ar=c(0.9)), n=n, innov=eps) and z1 <- arima.sim(list(ar=c(0.9)), n=n, sd=0.03), I would expect z0 and z1 to be qualitatively similar. However, with n=10 the