[R] add a point to regression line and cook's distance

[jonathan_li@agilent.com]

It is likely that the "true" relationship is nonlinear. There isn't a priori knowledge about linearity. In the small range where we do have enough data, the relationship
looks linear. Outside the range, the data are very scarse and have high level of noises too.
This is why adding (0,0) to the data can potentially improve the fit a great deal. But at the
same time, I have never heard people doing it this way. 

Jonathan

-----Original Message-----
From: Murray Jorgensen [mailto:maj at stats.waikato.ac.nz]
Sent: Wednesday, December 03, 2003 5:18 PM
To: Wiener, Matthew
Cc: jonathan_li at agilent.com; r-help at stat.math.ethz.ch
Subject: Re: [R] add a point to regression line and cook's distance


Not a good idea, unless the regression function is *known* to be linear. 
More likely it is only approximately linear over small ranges.

Murray Jorgensen

Wiener, Matthew wrote:

> If you know that the line should pass through (0,0), would it make sense to
> do a regression without an intercept?  You can do that by putting "-1" in
> the formula, like:  lm(y ~ x - 1).
> 
> Hope this helps,
> 
> Matt
> 
> Matthew Wiener
> RY84-202
> Applied Computer Science & Mathematics Dept.
> Merck Research Labs
> 126 E. Lincoln Ave.
> Rahway, NJ 07065
> 732-594-5303 
> 
> 
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Spencer Graves
> Sent: Wednesday, December 03, 2003 5:51 PM
> To: jonathan_li at agilent.com
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] add a point to regression line and cook's distance
> 
> 
>       What is the context?  What do the "outliers" represent?  If you 
> think carefully about the context, you may find the answer. 
> 
>       hope this helps.  spencer graves
> p.s.  I know statisticians who worked for HP before the split and who 
> still work for either HP or Agilent, I'm not certain which.  If you want 
> to contact me off-line, I can give you a couple of names if that might 
> help. 
> 
> jonathan_li at agilent.com wrote:
> 
> 
>>Hi, 
>>
>>This is more a statistics question rather than R question. But I thought
> 
> people on this list may have some pointers.
> 
>>MY question is like the following:
>>I would like to have a robust regression line. The data I have are mostly
> 
> clustered around a small range. So
> 
>>the regression line tend to be influenced strongly by outlier points (with
> 
> large cook's distance). From the application
> 
>>'s background, I know that the line should pass (0,0), which is far away
> 
> from the data cloud. I would like to add this
> 
>>point to have a more robust line. The question is: does it make sense to do
> 
> this? what are the negative impacts if any?
> 
>>thanks,
>>jonathan
>>
>>______________________________________________
>>R-help at stat.math.ethz.ch mailing list
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>> 
>>
> 
> 
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-- 
Dr Murray Jorgensen      http://www.stats.waikato.ac.nz/Staff/maj.html
Department of Statistics, University of Waikato, Hamilton, New Zealand
Email: maj at waikato.ac.nz                                Fax 7 838 4155
Phone  +64 7 838 4773 wk    +64 7 849 6486 home    Mobile 021 1395 862