[R-SIG-Finance] How to output "Trace" list from auto.arima in forecast library

[Arun Krishnamoorthy]

Hi,
I'm working on the forecast library and am using the auto.arima function
with some dummy data

Fit<-auto.arima(data_ts, trace=TRUE)

I understand that trace evaluates alternative models and provides the
corresponding AIC/SIC values with an output that looks like this;

ARIMA(2,1,2) with drift         : 1278.988
 ARIMA(0,1,0) with drift         : 1281.161
 ARIMA(1,1,0) with drift         : 1280.325
 ARIMA(0,1,1) with drift         : 1278.2
 ARIMA(1,1,1) with drift         : 1280.229
 ARIMA(0,1,2) with drift         : 1278.824
 ARIMA(1,1,2) with drift         : 1281.911
 ARIMA(0,1,1)                    : 1277.73
 ARIMA(1,1,1)                    : 1279.804
 ARIMA(0,1,0)                    : 1281.265
 ARIMA(0,1,2)                    : 1278.626
 ARIMA(1,1,2)                    : 1281.64

 Best model: ARIMA(0,1,1)              

Unfortunately, Trace is not an object and i'm unable to read it in to a data
frame to do further diagnosis.

Can someone please help me with how i can get this output into a data frame.
I'm unable to do data.frame since i can't coerce an ARIMA object into this
class.

Sorry if this has been addressed before. I just think there may be some data
series where running a closely competing alternative model may be useful

Thanks,
AK

-----Original Message-----
From: r-sig-finance-bounces at r-project.org
[mailto:r-sig-finance-bounces at r-project.org] On Behalf Of Daniel Cegielka
Sent: 26 September 2011 17:20
To: chrisbird
Cc: r-sig-finance at r-project.org
Subject: Re: [R-SIG-Finance] Filtering dates/times from zoo/xts series

2011/9/26 chrisbird <chris at chrisbird.com>

> Thanks Brian,
>
> I did try using the ['T09:00/T21:00'] method for extraction but it did not
> return anything - I will reinvestigate this and see if I can get it
> working.
>
>
It works... you are sure that the data was ok? Very strange that you have
received nothing...

> d<-xts(1:25, Sys.time() + 1:25)> d                    [,1]
2011-09-26 13:26:55    1
2011-09-26 13:26:56    2
2011-09-26 13:26:57    3
2011-09-26 13:26:58    4
2011-09-26 13:26:59    5
2011-09-26 13:27:00    6
2011-09-26 13:27:01    7
2011-09-26 13:27:02    8
2011-09-26 13:27:03    9
2011-09-26 13:27:04   10
2011-09-26 13:27:05   11
2011-09-26 13:27:06   12
2011-09-26 13:27:07   13
2011-09-26 13:27:08   14
2011-09-26 13:27:09   15
2011-09-26 13:27:10   16
2011-09-26 13:27:11   17
2011-09-26 13:27:12   18
2011-09-26 13:27:13   19
2011-09-26 13:27:14   20
2011-09-26 13:27:15   21
2011-09-26 13:27:16   22
2011-09-26 13:27:17   23
2011-09-26 13:27:18   24
2011-09-26 13:27:19   25> d["2011-09-26 13:27:00/2011-09-26 13:27:10"]
                   [,1]
2011-09-26 13:27:00    6
2011-09-26 13:27:01    7
2011-09-26 13:27:02    8
2011-09-26 13:27:03    9
2011-09-26 13:27:04   10
2011-09-26 13:27:05   11
2011-09-26 13:27:06   12
2011-09-26 13:27:07   13
2011-09-26 13:27:08   14
2011-09-26 13:27:09   15
2011-09-26 13:27:10   16> d["T13:27:00/T13:27:10"]                    [,1]
2011-09-26 13:27:00    6
2011-09-26 13:27:01    7
2011-09-26 13:27:02    8
2011-09-26 13:27:03    9
2011-09-26 13:27:04   10
2011-09-26 13:27:05   11
2011-09-26 13:27:06   12
2011-09-26 13:27:07   13
2011-09-26 13:27:08   14
2011-09-26 13:27:09   15
2011-09-26 13:27:10   16




> The processing is not to remove non-trading days/holidays - I do that
> elsewhere. I'm doing processing on some complex strategies which use some
> instruments which trade a lot, but not everyday. I only wish to process
the
> data from liquid days and strip out the less liquid data.
>
>
It's quite a sophisticated approach to data. Probably when you filter using
the time you would have to count the number of observations and does not
bind data below a certain level. I have no idea how to do it in an elegant
way.

best regards,
daniel



> I will certainly investigate quantstrat.
>
> Thanks,
>
> Chris.
>
>
> --
> View this message in context:
>
http://r.789695.n4.nabble.com/Filtering-dates-times-from-zoo-xts-series-tp38
42937p3843408.html
> Sent from the Rmetrics mailing list archive at Nabble.com.
>
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