Displaying 20 results from an estimated 9000 matches similar to: "ARIMA xreg and factors"
2008 Sep 10
2
arima and xreg
Dear R-help-archive..
I am trying to figure out how to make arima prediction when I have a
process involving multivariate time series input, and one output time
series (output is to be predicted) .. (thus strictly speaking its an
ARMAX process). I know that the arima function of R was not designed
to handle multivariate analysis (there is dse but it doesnt handle
arma multivariate analysis, only
2009 Mar 26
1
arima, xreg, and the armax model
Hello all,
I''m having fun again with the arima function. This time I read in:
http://www.stat.pitt.edu/stoffer/tsa2/R_time_series_quick_fix.htm
<<It has recently been suggested (by a reliable source) that using xreg in
arima() does NOT fit an ARMAX model [insert slap head icon here]. This will
be investigated as soon as time permits.>>
(by R.H. Shumway & D.S. Stoffer)
2008 Jan 11
1
question about xreg of arima
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
2004 May 02
1
arima problems when using argument fixed=
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)
2007 Aug 23
1
Estimate Intercept in ARIMA model
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))
2010 Mar 31
1
predict.Arima: warnings from xreg magic
When I run predict.Arima in my code, I get warnings like:
Warning message:
In cbind(intercept = rep(1, n), xreg) :
number of rows of result is not a multiple of vector length (arg 1)
I think this is because I'm not running predict.Arima in the same
environment that I did the fit, so the data object used in the fit is no
longer present. Looking at the predict.Arima source,
2008 Nov 27
1
"xreg" in ARIMA modelling.
Hello,
Does anyone know how the parameter estimates are calculated for xreg
variables when called as part of an arima() command, or know of any
literature that provides this info? In particular, I was wondering if there
is a quick way to compare different combinations of "xreg" variables in the
arima() fit in the same way that you would in multiple regression (using AIC
& R^2
2002 Oct 28
4
arima() in for loop
hi all,
In a simulation context I'm running in a for loop the arima() function
for( i in 1:1000){
y<-arima.sim(....)
out<-arima(y,....)
........
}
Everything works, but after some cycle (10, say) I get error due to the
particular y-values simulated. (E.g., a *frequent* error is "Error in
svd(na.omit(xreg)) : 0 extent dimensions") As a
2004 Mar 04
2
adding trend to an arima model
Hi,
Does anyone know a method for adding a linear/polynominal trend to a
simulated arima model using the arima.sim function?
Any help will be greatly appreciated.
Cheers,
Sam.
2005 Mar 05
4
How to use "lag"?
Is it possible to fit a lagged regression, "y[t]=b0+b1*x[t-1]+e",
using the function "lag"? If so, how? If not, of what use is the
function "lag"? I get the same answer from y~x as y~lag(x), whether
using lm or arima. I found it using y~c(NA, x[-length(x)])). Consider
the following:
> set.seed(1)
> x <- rep(c(rep(0, 4), 9), len=9)
> y <-
2003 Sep 01
1
Arima with an external regressor
Hello,
Does anybody know if the function arima with an external regressor (xreg)
applies the auto correlation on the dependant variable or on the residuals.
In comparison with SAS (proc autoreg), it seems that the auto correlation
applies on the residuals but i'd like to have the confirmation.
I want to estimate:
Y[t] = a[1]*X[t] + a[2] + E[t]
with E[t]=b[1]*E[t-1]
Should I use :
arima(Y,
2004 Jan 14
2
Fixed parameters in an AR (or arima) model
Hello
I want to fit an AR model were two of the coefficients are fixed to zero
(the second and third ar-coefficients).
I used the "arima" function with the "fixed" argument but the ar3
coefficient is not set to zero:
==============================================
> arima(Y, order=c(4,0,0), xreg=1:23, fixed=c(NA,0,0,NA,NA,NA))
Call:
arima(x = Y, order = c(4, 0, 0), xreg =
2012 Apr 26
1
Using the R predict function to forecast a model fit with auto.arima function
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
2004 Feb 04
1
arima function
Hello,
I am a beginner user of R and I would like to estimate a model with AR
errors. I use arima function:
modele
<-arima(conso,xreg=var.exogenes,order=c(ordre,0,0),include.mean=TRUE,method
="CSS")
My inputs are dummies for each month except one, and the same thing for
each day and each hour. I have this error message:
Warning message:
possible convergence problem: optim gave
2003 Apr 21
2
Anyone Familiar with Using arima function with exogenous variables?
I've posted this before but have not been able to locate what I'm doing
wrong. I cannot determine how the forecast is made using the estimated
coefficients from a simple AR(2) model when there is an exogenous
variable. Does anyone know what the problem is? The help file for arima
doesn't show the model with any exogenous variables. I haven't been able
to locate any documents
2008 Apr 17
1
How to extract vectors from an arima() object and into a data frame?
This should be very easy, but alas, I'm very new to R. My end goal is to
calculate p-values from arima().
Let's say I just ran this:
> MyModel <- arima(y[1:58], order=c(1,0,0), xreg=MyData[1:58,7:14],
> method="ML")
> MyModel
And I see:
arima(x = y[1:58], order = c(1, 0, 0), xreg = MyData[1:58, 7:14], method =
"ML")
Coefficients:
ar1
2011 Oct 21
2
Arima Models - Error and jump error
Hi people,
I´m trying to development a simple routine to run many Arima models result
from some parâmeters combination.
My data test have one year and daily level.
A part of routine is:
for ( d in 0:1 )
{ for ( p in 0:3 )
{ for ( q in 0:3 )
{ for ( sd in 0:1 )
{ for ( sp in 0:3 )
{ for ( sq in 0:3 )
{
2008 Sep 10
0
FW: RE: arima and xreg
hi: you should probably send below to R-Sig-Finance because there are
some econometrics people over there who could also possibly give you
a good answer and may not see this email ? Also, there's package called
mar ( I think that's the name ) that may do what you want ?
Finally, I don't know how to do it but I think there are ways of
converting a multivariate arima into the
2013 Mar 22
0
predict.Arima error "'xreg' and 'newxreg' have different numbers of columns"
Hello all,
I use arima to fit the model with
fit <- arima(y, order = c(1,0,1), xreg = list.indep, include.mean = TRUE)
and would like to use predict() to forecast:
chn.forecast <- rep(0,times=num.record)
chn.forecast[1] <- y[1]
for (j in 2:num.record){
indep <- c(aa=chn.forecast[j-1], list.indep[j,2:num.indep]) # this is the newxreg in the
2009 Nov 09
0
ARIMA, xreg and intercepts
David Stoffer describes some challenges with R's output when fitting
ARIMA models for different orders (see Issue 2 at
http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm). R doesn't fit an
intercept in the model if there is any differencing. David describes a
workaround using the xreg parameter to force R to calculate an
intercept.
Assume I have a variable y and 3 explanatory variables a,