similar to: Linear model mixed with an ARIMA model

Hi Im attempting to build a sample variogram for 300 obersvations of longitudinal data. So what I need to do is compute the half squared differences between pairs of residuals (for instance if a subject has 4 obersvations, this is 4 choose 2 paird differences) for each subject. Also, then I need the corresponding time differences within each individual. So the end result will be a 300 by 2

Hi all Does anyone know if it is possible when plotting a line or scatter plot, to selectively color the data points based on the data value? i.e. if plotting say the percentage change in stock price movements, to color +ve points in green and -ve points in red? And extending this to a user-defined range of colors based on the quartile of the data points? Thanks Rory Rory Winston RBS Global

Hello, I have a question about function arima.sim I tried to somulate a AR(1) process, with no innovation, no error term. I used this code: library(forecast) e=rnorm(100,mean=0,sd=0) series=arima.sim(model=list(ar=0.75),n=100,innov=e)+20 Then I tried to applicate ti this series auto.arima function: mod1<-auto.arima(series,stepwise=FALSE,trace=TRUE,ic='aicc') The best model returned

Dear all, When I run an arima(1,1,1) on an I(1) variable, e.g. y, I get different estimates to when I first difference the variable myself, e.g y2<-diff(y), and then run arima(1,0,1) on y2. Shouldn't these two approaches give the same output? Any help will be much appreciated. george -- View this message in context:

Dear all, When I run an arima(1,1,1) on an I(1) variable, y, I get different estimates to when I first difference the variable myself, e.g y2<-diff(y), and then run arima(1,0,1) on y2. Shouldn't these two approaches give the same output? Any help will be much appreciated. george

Hi, Vikram and I are beginning work on a native R package to interface into X-12-arima. We have looked through gretl, and previous discussions on kludgy interfaces involving calls to the x12a binary. Our aim is to port as much of the functionality as possible with native R objects, and to do away with the archaic file-based interface of X-12-arima. Our estimate is that

Why in arima output there is no significance tests of estimated parameters as in regression models? I know that I have s.e. and I could build these test by myself but are there any reasonable reasons? Best, Rob

Hello, I'm currently using auto.arima to verify the order of my arima model. I would like to use the model to conduct an intervention analysis. The problem is that, when I include a step function in auto.arima, by including a binary variable in "xreg", the arima order that auto.arima gives is different from when I don't include it. From my understanding, the

Hi Everyone, I'm having a problem with arima.sim. Namely specifying inital values for the series. If I generate a random walk > vs = rnorm(100,0,1) > xs = cumsum(vs) and fit an ARIMA(1,0,0) to it > xarima = arima(xs,order=c(1,0,0)) > xarima Call: arima(x = xs, order = c(1, 0, 0)) Coefficients: ar1 intercept 0.9895 8.6341 s.e. 0.0106 6.1869 I should

i am new to time series i found in help about arima arima(x = data, order = c(p, d, q)) what is exactly p,d,q? if i not changed them,what effects will happens? -- View this message in context: http://r.789695.n4.nabble.com/what-is-p-d-q-in-arima-function-of-time-series-tp4484368p4484368.html Sent from the R help mailing list archive at Nabble.com.

I have several hundred times series data sets and I am trying to use auto.arima(), in the forecasting package, to take a first stab at fitting an ARIMA model to each set. Ideally I would like to loop through each time series use auto.arima() to fit a model and output the R^2 of the model and the parameters. I know how to fit each model but I am having trouble generating the necessary output. I

I am having some issues with differencing using auto.arima when also specifying an xreg dataframe. The xreg dataframe contains dummy variables that specify time periods that had a promotion running. When I model diff(y) with order (1,0,1), the coefficients for these dummy variables are very different than when I model y with order=(1,1,1). I think when modeling diff(y) the coefficients

R 1.6.2 on windows XP (and windows 2000) Dear Readers, I have to fit an ARIMA model to a blood pressure series to make predictions with it. But since I don't have a blood pressure data set yet I have to work with self made data. So I have created an AR( 2 ) series with the following code: series <- list() series$series <- arima.sim(n=2100, model=list(ar = c(0.6, 0.1)), sd=1) + 120

Hi everyone, I'm trying to include an external regressor in my ARIMA model but am having some problems with the data format in R. I've named my dependent variable of interest "count" and the external regressor "abc". The external regressor is a binary variable. Here are the contents of "abc" and the model I've attemped (along with its error message):

Hi, I have to forecast some value of a time series using an ARIMA(5,1,3) model. I saw in Matlab there isn't a function for ARIMA models because ARIMA models are a type of Box-Jenkins models. But how to set parameters? In the Box-Jenkins models m = bj(data,[nb nc nd nf nk]) How to set nb, nc, nd, nf and nk in order to have an ARIMA(p,d,q) model? Thanks [[alternative HTML version

does the arima/arima0 function use the state space form of the model equation even when fitting with the "CSS"-method? regards Christoph [[alternative HTML version deleted]]