by Beyersmann, Jan, Allignol, Arthur, Schumacher, Martin
fromUse R!
Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount of data. Computational issues, though challenging, are no longer intractable. All that is needed is an entry point: thi…
Ideal for statisticians, this book will also interest probabilists, mathematicians, computer scientists, and morphometricians with mathematical training. It presents a systematic introduction to a general nonparametric theory of statistics on manifolds, with emphasis on manifold…
Density estimation -- Nonparametric regression -- Trend estimation -- Semiparametric regression -- Surface estimation
"The methods advanced in this book have their genesis in traditional nonparametrics. They incorporate the power of modern computers to make the approach more complete and more valid than previously possible. The authors' unified treatment and readable style make the subject easy…
