I agree with you on wavelets (although I’ve never had occasion to use them, I am fond of them). I do hope that the book emphasises the importance of ‘hard’ estimates in computational statistics (it’s not enough to just say that something converges, you need to know both how fast and whether it’s stable). Convergence in probability is lovely, but a bit vague (not a pun on modes of convergence) for practical purposes.

And I really hope there is a third edition, because there is a sore need for this sort of book. I’m particularly thrilled that there is a detailed section on numerical quadrature (I die a little every time I see someone use MC for a one or two dimensional integral…).

I am, however, a little curious about the selection of material in the first few chapters – I’d prefer a discussion of expansions in terms of orthogonal polynomials (Chebyshev series, Hermite expansions etc) and rational approximation over power series and continued fractions (!!), mainly because I have no idea where you’d use the latter two (I expect the book has better examples the ‘evaluation of special functions’).

]]>Kenneth Lange mentions in his introduction he keeps learning. So I am pretty sure that, if you mention the gaps to him, he will strive to include the better and more modern methods in his third edition. To me having wavelets included in such a general purpose book is a clear plus!

]]>Thanks Blaise, looks like there are a lot of changes from the first edition.

]]>What a shame! Maybe you should try contacting Springer directly…

]]>Thanks for using the link, I indeed get about 6% of the sale!!!

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