I have the following time series model for prediction purposes
*Loss_t = b1* Loss_(t-1) + b2*GDP_t + b3*W_(t-1)* where W_t is the
usual white noise variable.
So this is similar to ARMA(1,1) except that it also contains an extra
predictor, GDP at time t.
I have only 20 observations on eac
Check the package rugarch. It is capable of doing ARMA calculations with
external regressors
The woods are lovely, dark and deep
But I have promises to keep
And miles to go before I sleep
And miles to go before I sleep
-
On Thu, May 2, 2013 at 3:45 PM, Preetam Pal wrote:
> Hi,
>
> I want t
...@r-project.org] On
Behalf Of Preetam Pal
Sent: 02 May 2013 11:15
To: r-help@r-project.org
Subject: [R] ARMA with other regressor variables
Hi,
I want to fit the following model to my data:
Y_t= a+bY_(t-1)+cY_(t-2) + Z_t +Z_(t-1) + Z_(t-2) + X_t + M_t
i.e. it is an ARMA(2,2) with some additional regre
Hi,
I want to fit the following model to my data:
Y_t= a+bY_(t-1)+cY_(t-2) + Z_t +Z_(t-1) + Z_(t-2) + X_t + M_t
i.e. it is an ARMA(2,2) with some additional regressors X and M.
[Z_t's are the white noise variables]
How do I find the estimates of the coefficients in R?
And also I would like t
Hello,
Em 29-04-2013 13:49, Preetam Pal escreveu:
Hi all,
Suppose I am fitting an arma(p,q) model to a time series y_t.
So, my model should contain (q+1) white noise variables.
Why? How on hearth can you say this?
As far as I know, each of them should have the same variance.
How do I get th
Hi all,
Suppose I am fitting an arma(p,q) model to a time series y_t.
So, my model should contain (q+1) white noise variables.
As far as I know, each of them should have the same variance.
How do I get the estimate of this variance by running the arma(y) function
(or is there any other way)?
Appr
Hello,
This is a statistics question, not an R one.
If you want to fit an ARMA model, your time series can have any values,
zero, negative or positive. Please revise your knowledge of time series.
Hope this helps,
Rui Barradas
Em 28-02-2013 10:40, Nnina escreveu:
Hello,
I would like to comp
Hello,
I would like to compute ARMA and AR using arima-function in R.
My question is: If I have Null=zero values in my data, what should I do?
Remove ? or doesn't matter for ARIMA-models and I can estimate my
coefficients including zero values in data in arima-function in R ? What
is the better
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
In your first line, you write "ARMA(2,2)." However, what you fit in R is
ARIMA(2,1,2). What you fit in eview, I can't tell. Could that explain the
difference?
HTH,
Daniel
Young Gyu Park wrote:
>
> When I do ARMA(2,2) using one lag of LCPIH data
>
>
>
> This is eview result
>
>>
>> *Dependen
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
> **
On 06/07/11 13:28, Xiao Yang wrote:
Hi
I am new to time series analysis using R. does anyone know what the
estimated long term average of return means. I am doing an arma model
fitting of exchange rates, and the question I have been asked is to
estimate the long term average for the returns.
Hi
I am new to time series analysis using R. does anyone know what the
estimated long term average of return means. I am doing an arma model
fitting of exchange rates, and the question I have been asked is to
estimate the long term average for the returns. Is this same as the
intercept term? I
boki2b wrote:
>
> 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
> (w
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
Hi all,
I got the daily stock return data from 2005 - 2008, calculated from HF
minute data. (Thanks to Jeff and Josh).
Now, I set 05 - 07yr as the carlibration period for estimating the
parameters of ARMA(1,1)-GARCH(1,1) model, aqnd leave 08 for backtesting.
So I use the return data observations
Function arma is crashing in some (pathological, but crashing is never good)
cases.
For example:
library(tseries)
arma(c(2.01, 2.22, 2.09, 2.17, 2.42), order=c(1,0))
I came to that pathological series while doing test cases; probably there
are crashing cases with longer series.
Alberto Montei
"JM" == Joseph Magagnoli
on Wed, 29 Apr 2009 14:54:26 -0500
JM> > garchFit(formula.mean= ~arma(2,2),formula.var=~garch(1,1),
JM> data=data1)
JM> Error in garchFit(formula.mean = ~arma(2, 2), formula.var =
JM> ~garch(1, :
JM> element 1 is empty;
JM> the part of the args
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=
Hello,
Does anyone know about an R-package on multivariate ARMA-GARCH models? Or in
Matlab?
I would be very grateful if someone could help!
Thanks a lot!
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R-help@r-project.org mailing list
h
Raphael Saldanha wrote:
Hi!
Is there any package or function on R to ARMA models (Box & Jenkins, without
sazonality and trend) with resources to automatic identification for p and q
?
Have a look at auto.arima() from the forecast package
http://cran.ms.unimelb.edu.au/web/packages/forecasting/
Hi!
Is there any package or function on R to ARMA models (Box & Jenkins, without
sazonality and trend) with resources to automatic identification for p and q
?
Regards,
Raphael Saldanha
Brazil
[[alternative HTML version deleted]]
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R-help@r-
Dear ALL:
Could you please eamil me how to simulate Mixed Seasonal ARMA (p,q)x(P,Q)12
models [say ARMA(0,1)x(1,0)12 ]from R.
With many thanks.
Abou
==
AbouEl-Makarim Aboueissa, Ph.D.
Assistant Professor of Statistics
Department of Mathematics & Statistics
Univ
On Wed, 20 Aug 2008, Prof Brian Ripley wrote:
On Wed, 20 Aug 2008, Alberto Monteiro wrote:
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.
It is using asymptotic normali
On Wed, 20 Aug 2008, Alberto Monteiro wrote:
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.
It is using asymptotic normality. There is no exact theory. Who
mentioned S
Alberto Monteiro wrote:
> 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
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)
Call:
arma(x = x, order = c(1, 0))
Hi,
As far as I can tell, your code looks very similar to the example of
the paper "Parameter Estimation of ARMA Models with GARCH/APARCH
Errors" available at the rmetrics website. In this paper you can also
find an example how to calculate the hessian matrix.
What is the dataset and the paramete
Hello R-list-members,
I'm trying to model ARMA(0,2) & GARCH(1,1) process using the code below, but
according to my textbook, the estimated parameters are wrong. The MA-parameters
should be negative. (I've got the same problem using garchFit()). Can anyone
tell me what I'm doing wrong? And how ca
Hi, All:
Is there a way to get random effects for ARMA parameters?
Consider the following example from the 'corARMA' help page:
fm1Ovar.lme <- lme(follicles ~ sin(2*pi*Time) + cos(2*pi*Time),
data = Ovary, random = pdDiag(~sin(2*pi*Time)))
fm5Ovar.lme <- update(fm
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