Here is a link to a fascinating presentation by Harvey Stein ("Risky Measures of Risk: Error Analysis of Numerical Differentiation").
He makes a very "visual" case for why one needs to think carefully before using large (convexity error) or small step sizes (cancellation error).
He makes a very "visual" case for why one needs to think carefully before using large (convexity error) or small step sizes (cancellation error).
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