🚀 go-pugleaf

Just wondering - in using a biased estimator in the usual linear    
regression model given by

                         y = Xb + e

it's often possible to come up with an expression (as in principal
component regression, for example) for the bias of the estimator.
Unfortunately, it usually depends on b, the unknown parameter of
interest.  My question is this:  are there any methods to estimate
the bias given an analytical expression for it, even if that
expression depends on b?  I came across an article in the latest
Technometrics in which the authors show how bootstrapping can be
used to estimate bias, but I'm looking for simple methods that are
not computationally intensive.

Any suggestions or pointers to references would be appreciated.

Aloke Phatak

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 | Aloke Phatak                                                               |
 | Department of Chemical Engineering                                         |
 | University of Waterloo                        phatak@watserv1.uwaterloo.ca |
 | Waterloo, Ontario CANADA N2L 3G1                 (519) 885-1211, ext. 6982 | 
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