R help - Sep 2017 - Interesting behavior of lm() with small, problematic data sets

> I think what you're seeing is
> https://en.wikipedia.org/wiki/Loss_of_significance.
Almost. 
All the results in the OP's summary are reflections of finite precision in
the analytically exact solution, leading to residuals smaller than the double
precision limit. The summary is correctly warning that it's all potentially
nonsense, and indeed the only things you can trust are the coefficient values
(to within .Machine$double.eps or thereabouts)

Interestingly, though, my current version of R (3.4.0) gives numerically exact
coefficients (c(1,0) and identically zero standard errors.

So this particular example is apparently version-specific.

S Ellison


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This email and any attachments are confidential. Any use...{{dropped:8}}

Indeed (version-specific).

With R 3.4.1 on linux, I get coefficients and residuals that are
numerically exact, F-statistic = NaN, p-value = NA, R-squared = NaN, etc.

All of which is what ought to happen, given that the response variable
(y) is not actually variable.


---JRG
John R. Gleason


On 09/06/2017 09:10 AM, S Ellison wrote:
>> I think what you're seeing is
>> https://en.wikipedia.org/wiki/Loss_of_significance.
> 
> Almost. 
> All the results in the OP's summary are reflections of finite precision
in the analytically exact solution, leading to residuals smaller than the double
precision limit. The summary is correctly warning that it's all potentially
nonsense, and indeed the only things you can trust are the coefficient values
(to within .Machine$double.eps or thereabouts)
> 
> Interestingly, though, my current version of R (3.4.0) gives numerically
exact coefficients (c(1,0) and identically zero standard errors.
> 
> So this particular example is apparently version-specific.
> 
> S Ellison
> 
> 
> *******************************************************************
> This email and any attachments are confidential. Any use...{{dropped:8}}
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

Same version on Mac, same results.

> On 6 Sep 2017, at 15:22, JRG <loesljrg at accucom.net> wrote:
> 
> Indeed (version-specific).
> 
> With R 3.4.1 on linux, I get coefficients and residuals that are
> numerically exact, F-statistic = NaN, p-value = NA, R-squared = NaN, etc.
> 
> All of which is what ought to happen, given that the response variable
> (y) is not actually variable.
> 
> 
> ---JRG
> John R. Gleason
> 
> 
> On 09/06/2017 09:10 AM, S Ellison wrote:
>>> I think what you're seeing is
>>> https://en.wikipedia.org/wiki/Loss_of_significance.
>> 
>> Almost. 
>> All the results in the OP's summary are reflections of finite
precision in the analytically exact solution, leading to residuals smaller than
the double precision limit. The summary is correctly warning that it's all
potentially nonsense, and indeed the only things you can trust are the
coefficient values (to within .Machine$double.eps or thereabouts)
>> 
>> Interestingly, though, my current version of R (3.4.0) gives
numerically exact coefficients (c(1,0) and identically zero standard errors.
>> 
>> So this particular example is apparently version-specific.
>> 
>> S Ellison
>> 
>> 
>> *******************************************************************
>> This email and any attachments are confidential. Any
use...{{dropped:8}}
>> 
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>> 
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.