Message-ID: <alpine.LFD.2.00.0902161932210.26064@gannet.stats.ox.ac.uk>
Date: 2009-02-16T19:33:49Z
From: Brian Ripley
Subject: assuming AR(1) residuals in OLS
In-Reply-To: <CD693848-B381-4A93-B5AB-A63F3EBAC03D@virginia.edu>
You will need
library(nlme)
first.
But not for ?arima, which seems the more obvious way to do this simple
example.
On Mon, 16 Feb 2009, Michael Kubovy wrote:
> ?gls
>
> On Feb 16, 2009, at 12:28 PM, constantine wrote:
>
>> In other statistical software, such as Eviews, it is possible to
>> regress a model with the Least Squares method, assuming that the
>> residuals follow an AR(q) process.
>> For example the resulting regression is something like
>>
>> y = 1.2154 + 0.2215 x + 0.251 AR(1)
>>
>> How is it possible to do the same in R?
>
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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