Re: [R] assuming AR(1) residuals in OLS

Thank you Gabor Grothendieck for your message. I would surely like to say, that if someone wants to assume AR(1) residuals, running the regression y ~ x, could run gls(y~x, correlation = corAR1(0, ~1)) Constantine Tsardounis http://www.costis.name

Re: [R] assuming AR(1) residuals in OLS

Thank you for the lightening replies. I tested various corStruct objects (?corClasses) using the nlme package and all work flawlessly. My best regards to all... Constantine Tsardounis __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/l

Re: [R] assuming AR(1) residuals in OLS

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

Re: [R] assuming AR(1) residuals in OLS

?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

[R] assuming AR(1) residuals in OLS

Hi to all, 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 th