10:31 a.m.
Greetings,
1) Can you suggest an easy way to search the gretl-users archive?
2) Using the Gretl GUI, can I perform a classical decomposition similar to
that performed by Minitab (e.g., see Chapter 7 of Minitab 13 manual)?
3) If I can't do it with the GUI, can you offer some guidance on how to use
the command line to do this?
Thanks for the help.
Tom
10:41 a.m.
Am 01.02.2008 11:31, Tom La Bone schrieb:
Greetings,
1) Can you suggest an easy way to search the gretl-users archive?
No, and it would be welcome.
2) Using the Gretl GUI, can I perform a classical decomposition similar
to that performed by Minitab (e.g., see Chapter 7 of Minitab 13 manual)?
Forgive my ignorance, I don't know what it is, and not everybody has the
Mintiab manual.
-sven
10:50 a.m.
Classical decomposition is breaking a univariate times series down into a
trend component, a seasonal component, and a random noise component (for
example, see Chapter 1 of Brockwell and Davis intro to time series book).
Tom
-----Original Message-----
From: Sven Schreiber [mailto:svetosch@gmx.net]
Sent: Friday, February 01, 2008 5:41 AM
To: labone(a)gforcecable.com; Gretl list
Subject: Re: [Gretl-users] Classical Decomposition
Am 01.02.2008 11:31, Tom La Bone schrieb:
Greetings,
1) Can you suggest an easy way to search the gretl-users archive?
No, and it would be welcome.
2) Using the Gretl GUI, can I perform a classical decomposition similar
to that performed by Minitab (e.g., see Chapter 7 of Minitab 13 manual)?
Forgive my ignorance, I don't know what it is, and not everybody has the
Mintiab manual.
-sven
10:59 a.m.
Am 01.02.2008 11:50, Tom La Bone schrieb:
Classical decomposition is breaking a univariate times series down
into a
trend component, a seasonal component, and a random noise component (for
example, see Chapter 1 of Brockwell and Davis intro to time series book).
Tom
For a reasonable (IMHO) definition of trend component that is only
possible if you replace "random noise component" by "stationary
component".
So I am still not entirely sure, but I suspect you may want to do
Box-Jenkins ARIMA modeling. (Model->Time Series->Arima)
HTH,
sven
11:06 a.m.
El Friday 01 February 2008 11:50:41 Tom La Bone escribió:
Classical decomposition is breaking a univariate times series down
into a
trend component, a seasonal component, and a random noise component (for
example, see Chapter 1 of Brockwell and Davis intro to time series book).
Tom
You have the Hodrick-Prescott and Baxter-King filters to get the trend. We
currently don't have a native decomposition procedure.
I wrote a gretl package for decomposing a time series based in the structural
models framework (see Harvey's "Time series Models" or "Forecasting
structural time series models and the Kalman filter"). It is in a very
"beta"
state, so it is not finished and it is very slow (I will send it to you in a
private message).
Jack is working in a user interface for the Kalman filter which may do this
things to estimate faster.
But it is work in progress ...
--
Ignacio Diaz-Emparanza
DEPARTAMENTO DE ECONOMÍA APLICADA III (ECONOMETRÍA Y ESTADÍSTICA)
UPV/EHU
Avda. Lehendakari Aguirre, 83 | 48015 BILBAO
T.: +34 946013732 | F.: +34 946013754
www.et.bs.ehu.es
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participants (3)
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Ignacio Diaz-Emparanza -
Sven Schreiber -
Tom La Bone