[R] lm: how are polynomial functions interpreted?

[Carl Witthoft]

Well..... *_* ,

I think it should have been clear that this was not a question for which 
any code exists.  In fact, I gave two very specific examples of function 
calls.  The entire point of my question was not "what's up with my 
(putative) code and data " but rather to try to understand the 
overarching philosophy of the way lm() treats the function it's given.

I do understand the sneaky ways to make it do a linear fit with or 
without forcing the origin.  And, sure, I could have run a data set thru 
a bunch of different quadratic-like functions to try to see what happens.

Let me pick a more complicated example.  The general case of a sin fit 
might be Y = a + b*sin(d*x+phi)  .(where, to be pedantic, x is the only 
data input. All others are coefficients to be found)

If I try  y<-lm(yin~I(sin(x))), what is the actual fit function?  And so on.

That's why I was hoping for a more general explanation of what lm() does.



Charles C. Berry wrote:
> On Mon, 12 Jan 2009, cgw at witthoft.com wrote:
> 
> [nothing deleted]
> 
> matplot(1:100, lm(rnorm(100)~poly(1:100,4),x=T)$x ) # for example
> 
>>
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> Ahem!
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>> and provide commented, minimal, self-contained, reproducible code.
> ......^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
> 
> Charles C. Berry                            (858) 534-2098
>                                             Dept of Family/Preventive 
> Medicine
> E mailto:cberry at tajo.ucsd.edu                UC San Diego
> http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901
> 
> 
>