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 G. D'Agostini - arXiv
Triggered by a recent interesting article on the too frequent incorrect use of probabilistic evidence in courts, the author introduces the basic concepts of probabilistic inference with a toy model, and discusses several important issues.
by Arak M. Mathai, Hans J. Haubold - De Gruyter Open
This is an introduction to concepts of probability theory, probability distributions relevant in the applied sciences, as well as basics of sampling distributions, estimation and hypothesis testing. Designed for students in engineering and physics.
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 David A. Kenny - John Wiley & Sons Inc
This text is a general introduction to the topic of structural analysis. It presumes no previous acquaintance with causal analysis. It is general because it covers all the standard, as well as a few nonstandard, statistical procedures.