[R] updating observations in lm

[Roger Koenker]

The essential trick here is the Sherman-Morrison-Woodbury formula.  
My quantreg package has a lm.fit.recursive function that implements
a fortran version for adding observations, but like biglm I don't remove
observations at the other end either.

Roger Koenker
rkoenker at illinois.edu




On May 27, 2013, at 2:07 PM, Greg Snow wrote:

> Look at the biglm package.  It does 2 of the 3 things that you asked for:
> Construct an initial lm fit and add a new block of data to update that
> fit.  It does not remove data, but you may be able to look at the code and
> figure out a way to modify it to do the final piece.
> 
> 
> On Mon, May 27, 2013 at 9:12 AM, ivo welch <ivo.welch at anderson.ucla.edu>wrote:
> 
>> dear R experts---I would like to update OLS regressions with new
>> observations on the front of the data, and delete some old
>> observations from the rear.  my goal is to have a "flexible"
>> moving-window regression, with a minimum number of observations and a
>> maximum number of observations.  I can keep (X' X) and (X' y), and add
>> or subtract observations from these two quantities myself, and then
>> use crossprod.
>> 
>> strucchange does recursive residuals, which is closely related, but it
>> is not designed for such flexible movable windows, nor primarily
>> designed to produce standard errors of coefficients.
>> 
>> before I get started on this, I just wanted to inquire whether someone
>> has already written such a function.
>> 
>> regards,
>> 
>> /iaw
>> ----
>> Ivo Welch (ivo.welch at gmail.com)
>> 
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>> 
> 
> 
> 
> -- 
> Gregory (Greg) L. Snow Ph.D.
> 538280 at gmail.com
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
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