R help - Aug 2012 - inquire a statistical terms

Dear all,

Is there any standard statistical terminology describing the points beyond
a confidence region? Obviously, the "outlier" is improper here. Please
help
me if you happens have the info.

Thanks you very much for your kindly help.

Best wishes,

Zhiqiu

	[[alternative HTML version deleted]]

??
A confidence region for what? Confidence regions refer to parameters
and functions of parameters (e.g. means of fitted values) and are
completely incommensurate with the scale of the data. It sounds like
you are confusing basic concepts (i.e. you don't really understand
what a confidence region is), a common but severe error made by those
with inadequate statistical knowledge.

Of course, maybe you do have something in mind that makes sense; but
then you need to clarify.

And as this has nothing to do with R, you should not post further on
this list. Try stats.stackexchange.com instead.

-- Bert

On Wed, Aug 8, 2012 at 12:21 PM, Zhiqiu Hu <zhiqiu.hu at gmail.com>
wrote:
> Dear all,
>
> Is there any standard statistical terminology describing the points beyond
> a confidence region? Obviously, the "outlier" is improper here.
Please help
> me if you happens have the info.
>
> Thanks you very much for your kindly help.
>
> Best wishes,
>
> Zhiqiu
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> 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.


-- 

Bert Gunter
Genentech Nonclinical Biostatistics

Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm

>Is there any standard statistical terminology describing the points beyond
> a confidence region? 
'data'?

Sounds flippant, but even for univariate location estimates (a case where
parameter estimates and data can be compared directly)  a lot of data points are
usually outside confidence regions, because confidence regions for parameters
(or response) are usually a good deal smaller than the dispersion of data used
to estimate them. Generally, though, parameters and their confidence regions
aren't necessarily in the same dimensions as the data, so it's not
meaningful to ask whether data are inside or outside the parameter confidence
region. (As a simple example, the gradient from simple linear regression has the
units of response/predictor, which is not the same units as the response or
predictor making up the data).

If you mean observations outside a prediction interval for future observations
then 'outlier' (with suitable qualification as to the criterion for
identifying points as such) is probably as good a description as any because the
points are outside the region in which your model predicts as likely.

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