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Re: Question about DurbinWatsonD

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  Re: Question about DurbinWatsonD Darren Glosemeyer <darreng@wolfram.com> - 2011-05-21 10:46 +0000

#2555 — Re: Question about DurbinWatsonD

On 5/20/2011 5:37 AM, Gilmar Rodriguez-pierluissi wrote:
> In:
>
> http://reference.wolfram.com/mathematica/RegressionCommon/ref/DurbinWatsonD.html
>
> it says that:
>
> "As of Version 7.0, DurbinWatsonD has become a property of LinearModelFit".
>
> But, when I evaluate:
>
> data = {{0.05, 90}, {0.09, 95}, {0.14, 110}, {0.17, 125}, {0.2, 140}, {0.21, 150}, {0.23, 175}, {0.25, 190}, {0.3, 210}, {0.35, 255}};
>
> LinearModelFit[data, {1, x^2}, x, RegressionReport ->  {DurbinWatsonD}]
>
> the above line will not produce the DurbinWatsonD value of 1.14 shown in the example on that web page.
>
> How can I then get the DurbinWatsonD value?
>
> Thank you!
>
> Gilmar Rodriguez Pierluissi
>

LinearModelFit operates differently than the Regress function did.  
LinearModelFit generates a FittedModel object from which results such as 
"DurbinWatsonD" can be obtained, so you could do the following:


data={{0.05, 90}, {0.09, 95}, {0.14, 110}, {0.17, 125}, {0.2, 140}, 
{0.21, 150}, {0.23, 175}, {0.25, 190}, {0.3, 210}, {0.35, 255}};

lm=LinearModelFit[data, {1, x^2}, x]

lm["DurbinWatsonD"]

The main advantage of this object-based approach over the way Regress 
operated is that you can get additional results after the fitting 
without having to re-fit the model.

http://reference.wolfram.com/mathematica/ref/LinearModelFit.html

contains a number of examples and the list of properties available for 
linear models.

Darren Glosemeyer
Wolfram Research

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