or bigger lags (without the r<350 limit).
Here the modified code: https://gist.github.com/911292
The question is, there are theoretical guarantees that the iterative
solution is the right solution?
Some hints/directions/books?
Matteo Bertini
[[altern
ist to store the key-value map.
It will be enough for testing and I'll use something better if needed.
Thanks,
Matteo Bertini
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Il giorno 30/dic/2010, alle ore 16.03, Simon Urbanek ha scritto:
> On Dec 30, 2010, at 7:50 AM, Matteo Bertini wrote:
>
>> I'm testing some modifications in arima.c.
>> I've noticed that a big internal array of double (rbar) is usually sparse
>> and I'd l
-value mappings?
Thanks,
Matteo Bertini
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Il 22-07-2009 16:26, Matteo Bertini ha scritto:
I have found a strange error:
> fit = Arima(flow, c(1,0,1), list(order=c(0,1,1), period=96*7))
Error in makeARIMA(trarma[[1L]], trarma[[2L]], Delta, kappa) :
maximum supported lag is 350
Is in fact quite common to have a lag > 350 using a
ard in traffic flow prediction litterature for
example).
Is there any reasons against doing what is suggested in the comment and
avoid the hardcoded limit?
Thanks,
Matteo Bertini
# https://svn.r-project.org/R/trunk/src/library/stats/src/arima.c
SEXP getQ0(SEXP sPhi, SEXP sTheta)
{
