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September 25th, 2007 Leave a comment Go to comments

Page 96 of David Cox’s 2006 Principles of Statistical
Inference has a very nice one-sentence summary of asymptotic theory:

[A]pproximations are derived on the basis that the amount of
information is large, errors of estimation are small, nonlinear
relations are locally linear and a central limit effect operates to
induce approximate normality of log likelihood derivatives.

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