Re: [R] How to fit ARMA model

2011-07-01 Thread Ben Bolker
UnitRoot akhussanov at gmail.com writes:

 
 Hello,
 I am having some problems with fitting an ARMA model to my time series data
 (randomly generated numbers). The thing is I have tried many packages
 [tseries, fseries, FitARMA etc.] and all of them giving very different
 results. I would appreciate if someone could post here what the best package
 is for my purpose. 
 Also, after having done the fitting, I would like to check for the model's
 adequacy. How can I do this?
 Thanks.

  It's hard to say without more detail -- we don't know what your
purpose is (beyond the general one of fitting an ARMA model to data).
I would say that when in doubt, if there is functionality in 'core' R --
the base and recommended packages -- that it is likely to be the most
stable and well tested.  (Not always true -- there are some very good
contributed packages, and sometimes the functions in R are missing
some advanced features -- but a good rule of thumb.)  So try ?arima.

 Another rule of thumb is that Venables and Ripley 2002 is a good
starting point (although again not necessarily as extensive as specialized
topics) for how do I do xxx in R?  See Chapter 14.

  As suggested in the help for ?arima, ?tsdiag is a generic function
to plot time series diagnostics

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Re: [R] How to fit ARMA model

2011-07-01 Thread Mike Marchywka




 From: bbol...@gmail.com
 Date: Fri, 1 Jul 2011 13:16:45 +
 Subject: Re: [R] How to fit ARMA model
 
 UnitRoot akhussanov at gmail.com writes:
 
  
  Hello,
  I am having some problems with fitting an ARMA model to my time series data
  (randomly generated numbers). The thing is I have tried many packages
  [tseries, fseries, FitARMA etc.] and all of them giving very different
  results. I would appreciate if someone could post here what the best package
  is for my purpose. 
  Also, after having done the fitting, I would like to check for the model's
  adequacy. How can I do this?
  Thanks.
 
   It's hard to say without more detail -- we don't know what your
 purpose is (beyond the general one of fitting an ARMA model to data).
 I would say that when in doubt, if there is functionality in 'core' R --
 the base and recommended packages -- that it is likely to be the most
 stable and well tested.  (Not always true -- there are some very good
 contributed packages, and sometimes the functions in R are missing
 some advanced features -- but a good rule of thumb.)  So try ?arima.
 
  Another rule of thumb is that Venables and Ripley 2002 is a good
 starting point (although again not necessarily as extensive as specialized
 topics) for how do I do xxx in R?  See Chapter 14.
 

I had to check my memory but IIRC wiki or other non-authoritative source
suggested that this is not much different than trying to design or analyze
an IIR (infinte impulse response) filter that is presumed excited with white 
noise. In such a case, the
power spectrum could be interpretted in terms of zero and pole ( zeroes
of denomintator) of the transfer function giving you some graphical info
to help develop intuition. 


It is not hard to make your own tests and sanity checks if you are just getting
started. 
( hand typed as my 'dohs machine is busy running malware  scans and this one R 
install
has a few issues ) 
x-runif(8192)
x1-c(x[-1],x[1])
x2-c(x1[-1],x1[1])

y=x+x1+x2
plot(log(abs(fft(y

makes bode plot ( if I have the name right) with zeroes at the root. Extension 
to
IIR case should be obvious. 







   As suggested in the help for ?arima, ?tsdiag is a generic function
 to plot time series diagnostics
 
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