Applied Nonparametric Regression
by Wolfgang Härdle
Publisher: Cambridge University Press 1992
Number of pages: 433
This book represents an optimally estimated common thread for the numerous topics and results in the fast-growing area of nonparametric regression. The user-friendly approach taken by the author has successfully smoothed out most of the formidable asymptotic elaboration in developing the theory. This is an excellent collection for both beginners and experts.
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by O. Melchert - arXiv
In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations (aka sequence of random experiments).
by J. C. Lemm - arXiv.org
A particular Bayesian field theory is defined by combining a likelihood model, providing a probabilistic description of the measurement process, and a prior model, providing the information necessary to generalize from training to non-training data.
by D. Koutsoyiannis - National Technical University of Athens
Contents: The utility of probability; Basic concepts of probability; Elementary statistical concepts; Special concepts of probability theory in geophysical applications; Typical univariate statistical analysis in geophysical processes; etc.
by Martin Hairer - arXiv
This text is an attempt to give a reasonably self-contained presentation of the basic theory of stochastic partial differential equations, taking for granted basic measure theory, functional analysis and probability theory, but nothing else.